Data Table Manager
n8n-io/n8n
Load before calling data-tables or parse-file. An agent skill from n8n-io/n8n.
Requirement planning to wave-based CSV execution pipeline. An agent skill from catlog22/Claude-Code-Workflow.
$ npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install catlog22/Claude-Code-Workflow csv-wave-pipeline --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/csv-wave-pipeline .claude/skills/csv-wave-pipeline && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "csv-wave-pipeline" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.codex/skills/csv-wave-pipeline into .claude/skills/csv-wave-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "csv-wave-pipeline", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/catlog22/Claude-Code-Workflow/tree/main/.codex/skills/csv-wave-pipelineType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install catlog22/Claude-Code-Workflow csv-wave-pipeline --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.codex/skills/csv-wave-pipeline .agents/skills/csv-wave-pipeline && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "csv-wave-pipeline" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.codex/skills/csv-wave-pipeline into .agents/skills/csv-wave-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "csv-wave-pipeline", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install catlog22/Claude-Code-Workflow csv-wave-pipeline --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.codex/skills/csv-wave-pipeline .cursor/skills/csv-wave-pipeline && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "csv-wave-pipeline" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.codex/skills/csv-wave-pipeline into .cursor/skills/csv-wave-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "csv-wave-pipeline", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/catlog22/Claude-Code-Workflow.git --path .codex/skills/csv-wave-pipeline--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install catlog22/Claude-Code-Workflow csv-wave-pipeline --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.codex/skills/csv-wave-pipeline .gemini/skills/csv-wave-pipeline && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "csv-wave-pipeline" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.codex/skills/csv-wave-pipeline into .gemini/skills/csv-wave-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "csv-wave-pipeline", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install catlog22/Claude-Code-Workflow csv-wave-pipelineInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .github/skills && cp -r skills-src/.codex/skills/csv-wave-pipeline .github/skills/csv-wave-pipeline && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "csv-wave-pipeline" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.codex/skills/csv-wave-pipeline into .github/skills/csv-wave-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "csv-wave-pipeline", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install catlog22/Claude-Code-Workflow csv-wave-pipeline --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.codex/skills/csv-wave-pipeline .opencode/skills/csv-wave-pipeline && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "csv-wave-pipeline" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.codex/skills/csv-wave-pipeline into .opencode/skills/csv-wave-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "csv-wave-pipeline", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
csv-wave-pipelineRequirement planning to wave-based CSV execution pipeline. An agent skill from catlog22/Claude-Code-Workflow.
CSV Wave Pipeline is an agent skill from catlog22/Claude-Code-Workflow. Requirement planning to wave-based CSV execution pipeline. Decomposes requirement into dependency-sorted CSV tasks, computes execution waves, runs wave-by-wave via spawnagentsoncsv with cross-wave context propagation.
Its SKILL.md is about 9.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Documents & Office, covering CSV and tabular files. The repository describes itself as: JSON-driven multi-agent cadence-team development framework with intelligent CLI orchestration (Gemini/Qwen/Codex), context-first architecture, and automated workflow execution. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 07491b0. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
spawn_agents_on_csvReadWriteEditBashGlobGreprequest_user_inputFrom allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript, bash, csv and jsonl).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
CSV Wave Pipeline loads about 9.7k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 1,056 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: spawn_agents_on_csv, Read, Write, Edit, Bash, Glob, Grep, request_user_inputAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from catlog22/Claude-Code-Workflow at commit 07491b0, republished under its MIT licence (© catlog22). 1,056 words, ~9,698 tokens.
.claude/skills/csv-wave-pipeline/SKILL.md (or your agent's skills folder).When --yes or -y: Auto-confirm task decomposition, skip interactive validation, use defaults.
$csv-wave-pipeline "Implement user authentication with OAuth, JWT, and 2FA"
$csv-wave-pipeline -c 4 "Refactor payment module with Stripe and PayPal"
$csv-wave-pipeline -y "Build notification system with email and SMS"
$csv-wave-pipeline --continue "auth-20260228"Flags:
-y, --yes: Skip all confirmations (auto mode)-c, --concurrency N: Max concurrent agents within each wave (default: 4)--continue: Resume existing sessionWave-based batch execution using spawn_agents_on_csv with cross-wave context propagation. Tasks are grouped into dependency waves; each wave executes concurrently, and its results feed into the next wave.
Core workflow: Decompose → Compute Waves → Execute Wave-by-Wave → Aggregate
Phase 1: Requirement → CSV
├─ Parse requirement into subtasks (3-10 tasks)
├─ Identify dependencies (deps column)
├─ Compute dependency waves (topological sort → depth grouping)
├─ Generate tasks.csv with wave column
└─ User validates task breakdown (skip if -y)
Phase 2: Wave Execution Engine
├─ For each wave (1..N):
│ ├─ Build wave CSV (filter rows for this wave)
│ ├─ Inject previous wave findings into prev_context column
│ ├─ spawn_agents_on_csv(wave CSV)
│ ├─ Collect results, merge into master tasks.csv
│ └─ Check: any failed? → skip dependents or retry
└─ discoveries.ndjson shared across all waves (append-only)
Phase 3: Results Aggregation
├─ Export final results.csv
├─ Generate context.md with all findings
├─ Display summary: completed/failed/skipped per wave
└─ Offer: view results | retry failed | doneTwo context channels flow across waves:
context_from column → prev_context injection — task-specific directed contextdiscoveries.ndjson — general exploration findings available to allWave 1 agents:
├─ Execute tasks (no prev_context)
├─ Write findings to report_agent_job_result
└─ Append discoveries to discoveries.ndjson
↓ merge results into master CSV
Wave 2 agents:
├─ Read discoveries.ndjson (exploration sharing)
├─ Read prev_context column (wave 1 findings from context_from)
├─ Execute tasks with full upstream context
├─ Write findings to report_agent_job_result
└─ Append new discoveries to discoveries.ndjson
↓ merge results into master CSV
Wave 3+ agents: same pattern, accumulated context from all prior waves.workflow/.csv-wave/{session-id}/
├── tasks.csv # Master state (updated per wave)
├── results.csv # Final results export (Phase 3)
├── discoveries.ndjson # Shared discovery board (all agents, append-only)
├── context.md # Human-readable report (Phase 3)
├── wave-{N}.csv # Temporary per-wave input (cleaned up after merge)
└── wave-{N}-results.csv # Temporary per-wave output (cleaned up after merge)| File | Purpose | Lifecycle |
|---|---|---|
tasks.csv | Master state — all tasks with status/findings | Updated after each wave |
wave-{N}.csv | Per-wave input with prev_context column | Created before wave, deleted after |
wave-{N}-results.csv | Per-wave output from spawn_agents_on_csv | Created during wave, deleted after merge |
results.csv | Final export of all task results | Created in Phase 3 |
discoveries.ndjson | Shared exploration board across all agents | Append-only, carries across waves |
context.md | Human-readable execution report | Created in Phase 3 |
id,title,description,test,acceptance_criteria,scope,hints,execution_directives,deps,context_from,wave,status,findings,files_modified,tests_passed,acceptance_met,error
"1","Setup auth module","Create auth directory structure and base files","Verify directory exists and base files export expected interfaces","auth/ dir created; index.ts and types.ts export AuthProvider interface","src/auth/**","Follow monorepo module pattern || package.json;src/shared/types.ts","","","","1","","","","","",""
"2","Implement OAuth","Add OAuth provider integration with Google and GitHub","Unit test: mock OAuth callback returns valid token; Integration test: verify redirect URL generation","OAuth login redirects to provider; callback returns JWT; supports Google and GitHub","src/auth/oauth/**","Use passport.js strategy pattern || src/auth/index.ts;docs/oauth-flow.md","Run npm test -- --grep oauth before completion","1","1","2","","","","","",""
"3","Add JWT tokens","Implement JWT generation and validation","Unit test: sign/verify round-trip; Edge test: expired token returns 401","generateToken() returns valid JWT; verifyToken() rejects expired/tampered tokens","src/auth/jwt/**","Use jsonwebtoken library; Set default expiry 1h || src/config/auth.ts","Ensure tsc --noEmit passes","1","1","2","","","","","",""
"4","Setup 2FA","Add TOTP-based 2FA with QR code generation","Unit test: TOTP verify with correct code; Test: QR data URL is valid","QR code generates scannable image; TOTP verification succeeds within time window","src/auth/2fa/**","Use speakeasy + qrcode libraries || src/auth/oauth/strategy.ts;src/auth/jwt/token.ts","Run full test suite: npm test","2;3","1;2;3","3","","","","","",""Columns:
| Column | Phase | Description |
|---|---|---|
id | Input | Unique task identifier (string) |
title | Input | Short task title |
description | Input | Detailed task description — what to implement |
test | Input | Test cases: what tests to write and how to verify (unit/integration/edge) |
acceptance_criteria | Input | Acceptance criteria: measurable conditions that define "done" |
scope | Input | Target file/directory glob — constrains agent work area, prevents cross-task file conflicts |
hints | Input | Implementation tips + reference files. Format: tips text || file1;file2. Before || = how to implement; after || = existing files to read before starting. Either part is optional |
execution_directives | Input | Execution constraints: commands to run for verification, tool restrictions, environment requirements |
deps | Input | Semicolon-separated dependency task IDs (empty = no deps) |
context_from | Input | Semicolon-separated task IDs whose findings this task needs |
wave | Computed | Wave number (computed by topological sort, 1-based) |
status | Output | pending → completed / failed / skipped |
findings | Output | Key discoveries or implementation notes (max 500 chars) |
files_modified | Output | Semicolon-separated file paths |
tests_passed | Output | Whether all defined test cases passed (true/false) |
acceptance_met | Output | Summary of which acceptance criteria were met/unmet |
error | Output | Error message if failed (empty if success) |
Each wave generates a temporary wave-{N}.csv with an extra prev_context column built from context_from by looking up completed tasks' findings in the master CSV:
id,title,description,test,acceptance_criteria,scope,hints,execution_directives,deps,context_from,wave,prev_context
"2","Implement OAuth","Add OAuth integration","Unit test: mock OAuth callback returns valid token","OAuth login redirects to provider; callback returns JWT","src/auth/oauth/**","Use passport.js strategy pattern || src/auth/index.ts;docs/oauth-flow.md","Run npm test -- --grep oauth","1","1","2","[Task 1] Created auth/ with index.ts and types.ts"
"3","Add JWT tokens","Implement JWT","Unit test: sign/verify round-trip; Edge test: expired token returns 401","generateToken() returns valid JWT; verifyToken() rejects expired/tampered tokens","src/auth/jwt/**","Use jsonwebtoken library; Set default expiry 1h || src/config/auth.ts","Ensure tsc --noEmit passes","1","1","2","[Task 1] Created auth/ with index.ts and types.ts"All agents across all waves share discoveries.ndjson. This eliminates redundant codebase exploration.
Lifecycle: Created by the first agent to write a discovery. Carries over across waves — never cleared. Agents append via echo '...' >> discoveries.ndjson.
Format: NDJSON, each line is a self-contained JSON:
{"ts":"2026-02-28T10:00:00+08:00","worker":"1","type":"code_pattern","data":{"name":"repository-pattern","file":"src/repos/Base.ts","description":"Abstract CRUD repository"}}
{"ts":"2026-02-28T10:01:00+08:00","worker":"2","type":"integration_point","data":{"file":"src/auth/index.ts","description":"Auth module entry","exports":["authenticate","authorize"]}}Discovery Types:
| type | Dedup Key | Description |
|---|---|---|
code_pattern | data.name | Reusable code pattern found |
integration_point | data.file | Module connection point |
convention | singleton | Code style conventions |
blocker | data.issue | Blocking issue encountered |
tech_stack | singleton | Project technology stack |
test_command | singleton | Test commands discovered |
Protocol Rules:
echo >> → don't batchconst getUtc8ISOString = () => new Date(Date.now() + 8 * 60 * 60 * 1000).toISOString()
// Parse flags
const AUTO_YES = $ARGUMENTS.includes('--yes') || $ARGUMENTS.includes('-y')
const continueMode = $ARGUMENTS.includes('--continue')
const concurrencyMatch = $ARGUMENTS.match(/(?:--concurrency|-c)\s+(\d+)/)
const maxConcurrency = concurrencyMatch ? parseInt(concurrencyMatch[1]) : 4
// Clean requirement text (remove flags — word-boundary safe)
const requirement = $ARGUMENTS
.replace(/--yes|(?:^|\s)-y(?=\s|$)|--continue|--concurrency\s+\d+|-c\s+\d+/g, '')
.trim()
let sessionId, sessionFolder
const slug = requirement.toLowerCase()
.replace(/[^a-z0-9\u4e00-\u9fa5]+/g, '-')
.substring(0, 40)
const dateStr = getUtc8ISOString().substring(0, 10).replace(/-/g, '')
sessionId = `cwp-${dateStr}-${slug}`
sessionFolder = `.workflow/.csv-wave/${sessionId}`
// Continue mode: find existing session
if (continueMode) {
const existing = Bash(`ls -t .workflow/.csv-wave/ 2>/dev/null | head -1`).trim()
if (existing) {
sessionId = existing
sessionFolder = `.workflow/.csv-wave/${sessionId}`
// Read existing tasks.csv, find incomplete waves, resume from there
const existingCsv = Read(`${sessionFolder}/tasks.csv`)
// → jump to Phase 2 with remaining waves
}
}
Bash(`mkdir -p ${sessionFolder}`)csv-wave-pipeline can receive structured context from analyze-with-file or workflow-lite-plan via handoff.json:
// Check if requirement references a prior analysis session
const handoffPathMatch = requirement.match(/handoff:(.+\.json)/)
let handoffContext = null
if (handoffPathMatch) {
const handoffPath = handoffPathMatch[1]
if (file_exists(handoffPath)) {
handoffContext = JSON.parse(Read(handoffPath))
// handoffContext: { source, session_id, summary, implementation_scope[], code_anchors[], key_findings[], exploration_artifacts{} }
// Enrich requirement with handoff context for CLI decomposition in Phase 1
requirement = `${handoffContext.summary}\n\n` +
`## Implementation Scope\n${handoffContext.implementation_scope.map((s, i) =>
`${i+1}. **${s.objective}** [${s.priority}]\n Files: ${s.target_files?.join(', ') || 'TBD'}\n Done when: ${s.acceptance_criteria?.join('; ') || 'TBD'}`
).join('\n')}\n\n` +
(handoffContext.key_findings?.length > 0
? `## Key Findings\n${handoffContext.key_findings.map(f => `- ${f.point || f}`).join('\n')}\n\n`
: '') +
(handoffContext.code_anchors?.length > 0
? `## Code Anchors\n${handoffContext.code_anchors.slice(0, 8).map(a => `- \`${a.file}:${a.lines}\`: ${a.significance}`).join('\n')}\n\n`
: '')
// Load exploration artifacts into discoveries.ndjson seed (if available)
if (handoffContext.exploration_artifacts?.exploration_codebase && file_exists(handoffContext.exploration_artifacts.exploration_codebase)) {
const codebaseData = JSON.parse(Read(handoffContext.exploration_artifacts.exploration_codebase))
const seedDiscoveries = [
...(codebaseData.patterns || []).map(p => JSON.stringify({
ts: getUtc8ISOString(), worker: 'handoff', type: 'code_pattern',
data: { name: p.pattern || p, file: p.files?.[0] || '', description: p.description || '' }
})),
...(codebaseData.relevant_files || []).slice(0, 5).map(f => JSON.stringify({
ts: getUtc8ISOString(), worker: 'handoff', type: 'integration_point',
data: { file: f.path, description: f.annotation || f.summary || '' }
}))
]
if (seedDiscoveries.length > 0) {
Write(`${sessionFolder}/discoveries.ndjson`, seedDiscoveries.join('\n') + '\n')
}
}
console.log(`[Handoff] Loaded from ${handoffContext.source} session ${handoffContext.session_id}: ${handoffContext.implementation_scope?.length || 0} scope items`)
}
}Usage with handoff:
$csv-wave-pipeline "handoff:.workflow/.analysis/ANL-2026-04-29-auth/handoff.json"
$csv-wave-pipeline -y "handoff:.workflow/.lite-plan/auth-plan/handoff.json"When handoff is provided:
implementation_scope[] enriches the CLI decomposition prompt in Phase 1 with pre-analyzed objectives, target files, and acceptance criteriacode_anchors[] give agents specific file:line entry pointsexploration_artifacts.exploration_codebase seeds discoveries.ndjson with known patterns and integration points, so Wave 1 agents skip redundant codebase exploration// Escape a value for CSV (wrap in quotes, double internal quotes)
function csvEscape(value) {
const str = String(value ?? '')
return str.replace(/"/g, '""')
}
// Parse CSV string into array of objects (header row → keys)
function parseCsv(csvString) {
const lines = csvString.trim().split('\n')
if (lines.length < 2) return []
const headers = parseCsvLine(lines[0]).map(h => h.replace(/^"|"$/g, ''))
return lines.slice(1).map(line => {
const cells = parseCsvLine(line).map(c => c.replace(/^"|"$/g, '').replace(/""/g, '"'))
const obj = {}
headers.forEach((h, i) => { obj[h] = cells[i] ?? '' })
return obj
})
}
// Parse a single CSV line respecting quoted fields with commas/newlines
function parseCsvLine(line) {
const cells = []
let current = ''
let inQuotes = false
for (let i = 0; i < line.length; i++) {
const ch = line[i]
if (inQuotes) {
if (ch === '"' && line[i + 1] === '"') {
current += '"'
i++ // skip escaped quote
} else if (ch === '"') {
inQuotes = false
} else {
current += ch
}
} else {
if (ch === '"') {
inQuotes = true
} else if (ch === ',') {
cells.push(current)
current = ''
} else {
current += ch
}
}
}
cells.push(current)
return cells
}Objective: Decompose requirement into tasks, compute dependency waves, generate tasks.csv.
Steps:
Decompose Requirement
// Use ccw cli to decompose requirement into subtasks
Bash({
command: `ccw cli -p "PURPOSE: Decompose requirement into 3-10 atomic tasks for batch agent execution. Each task must include implementation description, test cases, and acceptance criteria.
TASK:
• Parse requirement into independent subtasks
• Identify dependencies between tasks (which must complete before others)
• Identify context flow (which tasks need previous tasks' findings)
• For each task, define concrete test cases (unit/integration/edge)
• For each task, define measurable acceptance criteria (what defines 'done')
• Each task must be executable by a single agent with file read/write access
MODE: analysis
CONTEXT: @**/*
EXPECTED: JSON object with tasks array. Each task: {id: string, title: string, description: string, test: string, acceptance_criteria: string, scope: string, hints: string, execution_directives: string, deps: string[], context_from: string[]}.<tips> || <ref_file1>;<ref_file2>' (e.g. 'Use strategy pattern || src/base/Strategy.ts;docs/design.md')REQUIREMENT: ${requirement}" --tool gemini --mode analysis --rule planning-breakdown-task-steps`, run_in_background: true }) // Wait for CLI completion via hook callback // Parse JSON from CLI output → decomposedTasks[]
2. **Compute Waves** (Kahn's BFS topological sort with depth tracking)
```javascript
// Algorithm:
// 1. Build in-degree map and adjacency list from deps
// 2. Enqueue all tasks with in-degree 0 at wave 1
// 3. BFS: for each dequeued task at wave W, for each dependent D:
// - Decrement D's in-degree
// - D.wave = max(D.wave, W + 1)
// - If D's in-degree reaches 0, enqueue D
// 4. Any task without wave assignment → circular dependency error
//
// Wave properties:
// Wave 1: no dependencies — fully independent
// Wave N: all deps in waves 1..(N-1) — guaranteed completed before start
// Within a wave: tasks are independent → safe for concurrent execution
//
// Example:
// A(no deps)→W1, B(no deps)→W1, C(deps:A)→W2, D(deps:A,B)→W2, E(deps:C,D)→W3
// Wave 1: [A,B] concurrent → Wave 2: [C,D] concurrent → Wave 3: [E]
function computeWaves(tasks) {
const taskMap = new Map(tasks.map(t => [t.id, t]))
const inDegree = new Map(tasks.map(t => [t.id, 0]))
const adjList = new Map(tasks.map(t => [t.id, []]))
for (const task of tasks) {
for (const dep of task.deps) {
if (taskMap.has(dep)) {
adjList.get(dep).push(task.id)
inDegree.set(task.id, inDegree.get(task.id) + 1)
}
}
}
// BFS-based topological sort with depth tracking
const queue = [] // [taskId, depth]
const waveAssignment = new Map()
for (const [id, deg] of inDegree) {
if (deg === 0) {
queue.push([id, 1])
waveAssignment.set(id, 1)
}
}
let maxWave = 1
let idx = 0
while (idx < queue.length) {
const [current, depth] = queue[idx++]
for (const next of adjList.get(current)) {
const newDeg = inDegree.get(next) - 1
inDegree.set(next, newDeg)
const nextDepth = Math.max(waveAssignment.get(next) || 0, depth + 1)
waveAssignment.set(next, nextDepth)
if (newDeg === 0) {
queue.push([next, nextDepth])
maxWave = Math.max(maxWave, nextDepth)
}
}
}
// Detect cycles
for (const task of tasks) {
if (!waveAssignment.has(task.id)) {
throw new Error(`Circular dependency detected involving task ${task.id}`)
}
}
return { waveAssignment, maxWave }
}
const { waveAssignment, maxWave } = computeWaves(decomposedTasks)Generate tasks.csv
const header = 'id,title,description,test,acceptance_criteria,scope,hints,execution_directives,deps,context_from,wave,status,findings,files_modified,tests_passed,acceptance_met,error'
const rows = decomposedTasks.map(task => {
const wave = waveAssignment.get(task.id)
return [
task.id,
csvEscape(task.title),
csvEscape(task.description),
csvEscape(task.test),
csvEscape(task.acceptance_criteria),
csvEscape(task.scope),
csvEscape(task.hints),
csvEscape(task.execution_directives),
task.deps.join(';'),
task.context_from.join(';'),
wave,
'pending', // status
'', // findings
'', // files_modified
'', // tests_passed
'', // acceptance_met
'' // error
].map(cell => `"${String(cell).replace(/"/g, '""')}"`).join(',')
})
Write(`${sessionFolder}/tasks.csv`, [header, ...rows].join('\n'))User Validation (skip if AUTO_YES)
if (!AUTO_YES) {
// Display task breakdown with wave assignment
console.log(`\n## Task Breakdown (${decomposedTasks.length} tasks, ${maxWave} waves)\n`)
for (let w = 1; w <= maxWave; w++) {
const waveTasks = decomposedTasks.filter(t => waveAssignment.get(t.id) === w)
console.log(`### Wave ${w} (${waveTasks.length} tasks, concurrent)`)
waveTasks.forEach(t => console.log(` - [${t.id}] ${t.title}`))
}
const answer = functions.request_user_input({
questions: [{
header: "验证",
id: "validation",
question: "Approve task breakdown?",
options: [
{ label: "Approve(Recommended)", description: "Proceed with wave execution" },
{ label: "Modify", description: `Edit ${sessionFolder}/tasks.csv manually, then --continue` },
{ label: "Cancel", description: "Abort" }
]
}]
}) // BLOCKS
if (answer.answers.validation.answers[0] === "Modify") {
console.log(`Edit: ${sessionFolder}/tasks.csv\nResume: $csv-wave-pipeline --continue`)
return
} else if (answer.answers.validation.answers[0] === "Cancel") {
return
}
}Success Criteria: tasks.csv created with valid schema and wave assignments, no circular dependencies, user approved (or AUTO_YES).
Objective: Execute tasks wave-by-wave via spawn_agents_on_csv. Each wave sees previous waves' results.
Steps:
Wave Loop
const failedIds = new Set()
const skippedIds = new Set()
for (let wave = 1; wave <= maxWave; wave++) {
console.log(`\n## Wave ${wave}/${maxWave}\n`)
// 1. Read current master CSV
const masterCsv = parseCsv(Read(`${sessionFolder}/tasks.csv`))
// 2. Filter tasks for this wave
const waveTasks = masterCsv.filter(row => parseInt(row.wave) === wave)
// 3. Skip tasks whose deps failed
const executableTasks = []
for (const task of waveTasks) {
const deps = task.deps.split(';').filter(Boolean)
if (deps.some(d => failedIds.has(d) || skippedIds.has(d))) {
skippedIds.add(task.id)
updateMasterCsvRow(sessionFolder, task.id, {
status: 'skipped',
error: 'Dependency failed or skipped'
})
console.log(` [${task.id}] ${task.title} → SKIPPED (dependency failed)`)
continue
}
executableTasks.push(task)
}
if (executableTasks.length === 0) {
console.log(` No executable tasks in wave ${wave}`)
continue
}
// 4. Build prev_context for each task (from context_from → master CSV findings)
for (const task of executableTasks) {
const contextIds = task.context_from.split(';').filter(Boolean)
const prevFindings = contextIds
.map(id => {
const prevRow = masterCsv.find(r => r.id === id)
if (prevRow && prevRow.status === 'completed' && prevRow.findings) {
return `[Task ${id}: ${prevRow.title}] ${prevRow.findings}`
}
return null
})
.filter(Boolean)
.join('\n')
task.prev_context = prevFindings || 'No previous context available'
}
// 5. Write wave CSV
const waveHeader = 'id,title,description,test,acceptance_criteria,scope,hints,execution_directives,deps,context_from,wave,prev_context'
const waveRows = executableTasks.map(t =>
[t.id, t.title, t.description, t.test, t.acceptance_criteria, t.scope, t.hints, t.execution_directives, t.deps, t.context_from, t.wave, t.prev_context]
.map(cell => `"${String(cell).replace(/"/g, '""')}"`)
.join(',')
)
Write(`${sessionFolder}/wave-${wave}.csv`, [waveHeader, ...waveRows].join('\n'))
// 6. Execute wave
console.log(` Executing ${executableTasks.length} tasks (concurrency: ${maxConcurrency})...`)
const waveResult = spawn_agents_on_csv({
csv_path: `${sessionFolder}/wave-${wave}.csv`,
id_column: "id",
instruction: buildInstructionTemplate(sessionFolder, wave),
max_concurrency: maxConcurrency,
max_runtime_seconds: 600,
output_csv_path: `${sessionFolder}/wave-${wave}-results.csv`,
output_schema: {
type: "object",
properties: {
id: { type: "string" },
status: { type: "string", enum: ["completed", "failed"] },
findings: { type: "string" },
files_modified: { type: "array", items: { type: "string" } },
tests_passed: { type: "boolean" },
acceptance_met: { type: "string" },
error: { type: "string" }
},
required: ["id", "status", "findings", "tests_passed"]
}
})
// ↑ Blocks until all agents in this wave complete
// 7. Merge results into master CSV
const waveResults = parseCsv(Read(`${sessionFolder}/wave-${wave}-results.csv`))
for (const result of waveResults) {
updateMasterCsvRow(sessionFolder, result.id, {
status: result.status,
findings: result.findings || '',
files_modified: (result.files_modified || []).join(';'),
tests_passed: String(result.tests_passed ?? ''),
acceptance_met: result.acceptance_met || '',
error: result.error || ''
})
if (result.status === 'failed') {
failedIds.add(result.id)
console.log(` [${result.id}] ${result.title} → FAILED: ${result.error}`)
} else {
console.log(` [${result.id}] ${result.title} → COMPLETED`)
}
}
// 8. Cleanup temporary wave CSVs
Bash(`rm -f "${sessionFolder}/wave-${wave}.csv" "${sessionFolder}/wave-${wave}-results.csv"`)
console.log(` Wave ${wave} done: ${waveResults.filter(r => r.status === 'completed').length} completed, ${waveResults.filter(r => r.status === 'failed').length} failed`)
}Instruction Template Builder
function buildInstructionTemplate(sessionFolder, wave) {
return `Task ID: {id} Title: {title} Description: {description} Scope: {scope}
{hints}
Format: `
<tips>|| <ref_file1>;<ref_file2>`. Read ALL reference files (after ||) before starting implementation. Apply tips (before ||) as implementation guidance.
{execution_directives}
Commands to run for verification, tool restrictions, or environment requirements. Follow these constraints during and after implementation.
{test}
{acceptance_criteria}
{prev_context}
<ISO8601>","worker":"{id}","type":"<type>","data":{...}}' >> ${sessionFolder}/discoveries.ndjson
```Return JSON: { "id": "{id}", "status": "completed" | "failed", "findings": "Key discoveries and implementation notes (max 500 chars)", "files_modified": ["path1", "path2"], "tests_passed": true | false, "acceptance_met": "Summary of which acceptance criteria were met/unmet", "error": "" }
IMPORTANT: Set status to "completed" ONLY if:
Master CSV Update Helper
function updateMasterCsvRow(sessionFolder, taskId, updates) {
const csvPath = `${sessionFolder}/tasks.csv`
const content = Read(csvPath)
const lines = content.split('\n')
const header = lines[0].split(',')
for (let i = 1; i < lines.length; i++) {
const cells = parseCsvLine(lines[i])
if (cells[0] === taskId || cells[0] === `"${taskId}"`) {
// Update specified columns
for (const [col, val] of Object.entries(updates)) {
const colIdx = header.indexOf(col)
if (colIdx >= 0) {
cells[colIdx] = `"${String(val).replace(/"/g, '""')}"`
}
}
lines[i] = cells.join(',')
break
}
}
Write(csvPath, lines.join('\n'))
}Success Criteria: All waves executed in order, each wave's results merged into master CSV before next wave starts, dependent tasks skipped when predecessor failed, discoveries.ndjson accumulated across all waves.
Objective: Generate final results and human-readable report.
Steps:
Export results.csv
const masterCsv = Read(`${sessionFolder}/tasks.csv`)
// results.csv = master CSV (already has all results populated)
Write(`${sessionFolder}/results.csv`, masterCsv)Generate context.md
const tasks = parseCsv(masterCsv)
const completed = tasks.filter(t => t.status === 'completed')
const failed = tasks.filter(t => t.status === 'failed')
const skipped = tasks.filter(t => t.status === 'skipped')
const contextContent = `# CSV Batch Execution ReportSession: ${sessionId} Requirement: ${requirement} Completed: ${getUtc8ISOString()} Waves: ${maxWave} | Concurrency: ${maxConcurrency}
| Metric | Count |
|---|---|
| Total Tasks | ${tasks.length} |
| Completed | ${completed.length} |
| Failed | ${failed.length} |
| Skipped | ${skipped.length} |
| Waves | ${maxWave} |
${Array.from({ length: maxWave }, (_, i) => i + 1).map(w => {
const waveTasks = tasks.filter(t => parseInt(t.wave) === w)
return ### Wave ${w} ${waveTasks.map(t => - [${t.id}] ${t.title}: ${t.status}${t.tests_passed ? ' ✓tests' : ''}${t.error ? ' — ' + t.error : ''}
${t.findings ? 'Findings: ' + t.findings : ''}).join('\n')}
}).join('\n\n')}
${tasks.map(t => `### ${t.id}: ${t.title}
| Field | Value |
|---|---|
| Status | ${t.status} |
| Wave | ${t.wave} |
| Scope | ${t.scope |
| Dependencies | ${t.deps |
| Context From | ${t.context_from |
| Tests Passed | ${t.tests_passed |
| Acceptance Met | ${t.acceptance_met |
| Error | ${t.error |
Description: ${t.description}
Test Cases: ${t.test || 'N/A'}
Acceptance Criteria: ${t.acceptance_criteria || 'N/A'}
Hints: ${t.hints || 'N/A'}
Execution Directives: ${t.execution_directives || 'N/A'}
Findings: ${t.findings || 'N/A'}
Files Modified: ${t.files_modified || 'none'} `).join('\n---\n')}
${[...new Set(tasks.flatMap(t => (t.files_modified || '').split(';')).filter(Boolean))].map(f => '- ' + f).join('\n') || 'None'} `
Write(${sessionFolder}/context.md, contextContent)
3. **Display Summary**
```javascript
console.log(`
## Execution Complete
- **Session**: ${sessionId}
- **Waves**: ${maxWave}
- **Completed**: ${completed.length}/${tasks.length}
- **Failed**: ${failed.length}
- **Skipped**: ${skipped.length}
**Results**: ${sessionFolder}/results.csv
**Report**: ${sessionFolder}/context.md
**Discoveries**: ${sessionFolder}/discoveries.ndjson
`)Offer Next Steps (skip if AUTO_YES)
if (!AUTO_YES && failed.length > 0) {
const answer = functions.request_user_input({
questions: [{
header: "下一步",
id: "next_step",
question: `${failed.length} tasks failed. Next action?`,
options: [
{ label: "Retry Failed(Recommended)", description: `Re-execute ${failed.length} failed tasks with updated context` },
{ label: "View Report", description: "Display context.md" },
{ label: "Done", description: "Complete session" }
]
}]
}) // BLOCKS
if (answer.answers.next_step.answers[0] === "Retry Failed(Recommended)") {
// Reset failed tasks to pending, re-run Phase 2 for their waves
for (const task of failed) {
updateMasterCsvRow(sessionFolder, task.id, { status: 'pending', error: '' })
}
// Also reset skipped tasks whose deps are now retrying
for (const task of skipped) {
updateMasterCsvRow(sessionFolder, task.id, { status: 'pending', error: '' })
}
// Re-execute Phase 2 (loop will skip already-completed tasks)
// → goto Phase 2
} else if (answer.answers.next_step.answers[0] === "View Report") {
console.log(Read(`${sessionFolder}/context.md`))
}
}Success Criteria: results.csv exported, context.md generated, summary displayed to user.
| Error | Resolution |
|---|---|
| Circular dependency | Detect in wave computation, abort with error message |
| Agent timeout | Mark as failed in results, continue with wave |
| Agent failed | Mark as failed, skip dependent tasks in later waves |
| All agents in wave failed | Log error, offer retry or abort |
| CSV parse error | Validate CSV format before execution, show line number |
| discoveries.ndjson corrupt | Ignore malformed lines, continue with valid entries |
| Continue mode: no session found | List available sessions, prompt user to select |
deps = execution order constraint; context_from = information flow. A task can have context_from without deps (it just reads previous findings but doesn't require them to be done first in its wave)-c 1 for serial execution (maximum context sharing); -c 8 for I/O-bound tasks| Scenario | Recommended Approach |
|---|---|
| Independent parallel tasks (no deps) | $csv-wave-pipeline -c 8 — single wave, max parallelism |
| Linear pipeline (A→B→C) | $csv-wave-pipeline -c 1 — 3 waves, serial, full context |
| Diamond dependency (A→B,C→D) | $csv-wave-pipeline — 3 waves, B+C concurrent in wave 2 |
| Complex requirement, unclear tasks | Use $roadmap-with-file first for planning, then feed issues here |
| Single complex task | Use $workflow-lite-plan instead |
© catlog22, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .codex/skills/csv-wave-pipeline of catlog22/Claude-Code-Workflow.
Open the folder on GitHubat commit 07491b0
CSV Wave Pipeline next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| CSV Wave Pipeline this skillcatlog22/Claude-Code-Workflow | 2.1k | — | ~9.7k | Automated safety check: Notes | MIT | |
| Data Table Managern8n-io/n8n | 207k | — | ~2.3k | Automated safety check: Pass | Custom licence | |
| Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences | 274 | 2 repos | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Abuse Hunternexu-io/harness-engineering-guide | 664 | — | ~1.9k | Automated safety check: Pass | MIT | |
| Markitshift-labs-ai/markit | 1.3k | — | ~299 | Automated safety check: Pass | MIT | |
| Sector Analysttradermonty/claude-trading-skills | 3k | 1 repos | ~2.3k | Automated safety check: Pass | MIT |
n8n-io/n8n
Load before calling data-tables or parse-file. An agent skill from n8n-io/n8n.
aws-samples/amazon-bedrock-agents-healthcare-lifesciences
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV.
nexu-io/harness-engineering-guide
Detect and investigate bulk registration abuse on SaaS platforms.
shift-labs-ai/markit
Convert files and URLs to Markdown. An agent skill from shift-labs-ai/markit.
tradermonty/claude-trading-skills
This skill should be used when analyzing sector rotation patterns and market cycle positioning.
ckpxgfnksd-max/uap-release-analyzer
Inventory, extract, and analyze tranches of declassified UAP/UFO files — including war.gov/UFO/ "PURSUE" releases, FBI Vault, NARA boxes, and AARO publications.
catlog22/Claude-Code-Workflow
CCW command help system. An agent skill from catlog22/Claude-Code-Workflow.
catlog22/Claude-Code-Workflow
Unified brainstorming skill with dual-mode operation — auto mode (framework generation, parallel multi-role analysis, cross-role synthesis) and single role analysis.
catlog22/Claude-Code-Workflow
Chain-based CCW workflow orchestrator. An agent skill from catlog22/Claude-Code-Workflow.
catlog22/Claude-Code-Workflow
Check workflow delegation prompts against agent role definitions for content separation violations.
catlog22/Claude-Code-Workflow
Systematic debugging with Iron Law methodology. An agent skill from catlog22/Claude-Code-Workflow.
catlog22/Claude-Code-Workflow
Unified issue discovery and creation. An agent skill from catlog22/Claude-Code-Workflow.
Categories
Requirement planning to wave-based CSV execution pipeline. An agent skill from catlog22/Claude-Code-Workflow. CSV Wave Pipeline is an agent skill from catlog22/Claude-Code-Workflow. Requirement planning to wave-based CSV execution pipeline.
CSV Wave Pipeline fits situations like: tasks that involve CSV and tabular files.
Run `npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a claude-code`. Or copy the skill folder (.codex/skills/csv-wave-pipeline in catlog22/Claude-Code-Workflow) into .claude/skills/csv-wave-pipeline in your project. Claude Code loads it when a task matches its description.
Run `npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a codex`. Or copy the skill folder (.codex/skills/csv-wave-pipeline in catlog22/Claude-Code-Workflow) into .agents/skills/csv-wave-pipeline in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipeline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/csv-wave-pipeline, .gemini/skills/csv-wave-pipeline, .github/skills/csv-wave-pipeline and .opencode/skills/csv-wave-pipeline in your project.
SKILL.md names no scripts, command-line tools or credentials: CSV Wave Pipeline is instructions for the agent only. Its frontmatter pre-approves these tools: spawn_agents_on_csv, Read, Write, Edit, Bash, Glob, Grep, request_user_input.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
CSV Wave Pipeline is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 9.7k tokens (SKILL.md is roughly 39k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with CSV Wave Pipeline: Data Table Manager (n8n-io/n8n, 207k stars), Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Abuse Hunter (nexu-io/harness-engineering-guide, 664 stars) and Markit (shift-labs-ai/markit, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
catlog22 (a GitHub user) maintains it in catlog22/Claude-Code-Workflow, which has 2,130 GitHub stars. The repository holds 82 skills in this directory. The repository was last updated on June 18, 2026.
Source: catlog22/Claude-Code-Workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.