ccc Semantic Code Search
cocoindex-io/cocoindex-code
Semantic code search and index management with the ccc CLI: the agent initializes, indexes and queries the project by concept, filtering by language or path.
Multi-CLI collaborative planning with codebase context gathering, iterative cross-verification, and execution handoff.
$ npx skills add catlog22/Claude-Code-Workflow --skill workflow-multi-cli-plan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install catlog22/Claude-Code-Workflow workflow-multi-cli-plan --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/.claude/skills/workflow-multi-cli-plan .claude/skills/workflow-multi-cli-plan && 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 "workflow-multi-cli-plan" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.claude/skills/workflow-multi-cli-plan into .claude/skills/workflow-multi-cli-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "workflow-multi-cli-plan", 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/.claude/skills/workflow-multi-cli-planType 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 workflow-multi-cli-plan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install catlog22/Claude-Code-Workflow workflow-multi-cli-plan --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/.claude/skills/workflow-multi-cli-plan .agents/skills/workflow-multi-cli-plan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "workflow-multi-cli-plan" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.claude/skills/workflow-multi-cli-plan into .agents/skills/workflow-multi-cli-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "workflow-multi-cli-plan", 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 workflow-multi-cli-plan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install catlog22/Claude-Code-Workflow workflow-multi-cli-plan --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/.claude/skills/workflow-multi-cli-plan .cursor/skills/workflow-multi-cli-plan && 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 "workflow-multi-cli-plan" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.claude/skills/workflow-multi-cli-plan into .cursor/skills/workflow-multi-cli-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "workflow-multi-cli-plan", 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 .claude/skills/workflow-multi-cli-plan--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 workflow-multi-cli-plan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install catlog22/Claude-Code-Workflow workflow-multi-cli-plan --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/.claude/skills/workflow-multi-cli-plan .gemini/skills/workflow-multi-cli-plan && 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 "workflow-multi-cli-plan" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.claude/skills/workflow-multi-cli-plan into .gemini/skills/workflow-multi-cli-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "workflow-multi-cli-plan", 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 workflow-multi-cli-planInstalls 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 workflow-multi-cli-plan -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/.claude/skills/workflow-multi-cli-plan .github/skills/workflow-multi-cli-plan && 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 "workflow-multi-cli-plan" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.claude/skills/workflow-multi-cli-plan into .github/skills/workflow-multi-cli-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "workflow-multi-cli-plan", 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 workflow-multi-cli-plan -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 workflow-multi-cli-plan --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/.claude/skills/workflow-multi-cli-plan .opencode/skills/workflow-multi-cli-plan && 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 "workflow-multi-cli-plan" agent skill from https://github.com/catlog22/Claude-Code-Workflow/tree/main/.claude/skills/workflow-multi-cli-plan into .opencode/skills/workflow-multi-cli-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "workflow-multi-cli-plan", 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.
workflow-multi-cli-planMulti-CLI collaborative planning with codebase context gathering, iterative cross-verification, and execution handoff.
Workflow Multi CLI Plan is an agent skill from catlog22/Claude-Code-Workflow. Multi-CLI collaborative planning with codebase context gathering, iterative cross-verification, and execution handoff.
Its SKILL.md is about 3.9k 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 Agent Workflows, covering Codebase knowledge for agents. 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.
5 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:
SkillAgentAskUserQuestionTodoWriteReadWriteEditBashGlobGrepFrom allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript and json).
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.
Workflow Multi CLI Plan loads about 3.9k tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 352 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: Skill, Agent, AskUserQuestion, TodoWrite, Read, Write, Edit, Bash, Glob, GrepAutomated 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). 352 words, ~3,865 tokens.
.claude/skills/workflow-multi-cli-plan/SKILL.md (or your agent's skills folder).When workflowPreferences.autoYes is true: Auto-approve plan, use recommended solution and execution method (Agent, Skip review).
Context Source: ACE semantic search + Multi-CLI analysis
Output Directory: .workflow/.multi-cli-plan/{session-id}/
Default Max Rounds: 3 (convergence may complete earlier)
CLI Tools: @cli-discuss-agent (analysis), @cli-lite-planning-agent (plan generation)
Execution: Auto-hands off to workflow-lite-execute after plan approval
Phase 1: Context Gathering
└─ ACE semantic search, extract keywords, build context package
Phase 2: Multi-CLI Discussion (Iterative, via @cli-discuss-agent)
├─ Round N: Agent executes Gemini + Codex + Claude
├─ Cross-verify findings, synthesize solutions
├─ Write synthesis.json to rounds/{N}/
└─ Loop until convergence or max rounds
Phase 3: Present Options
└─ Display solutions with trade-offs from agent output
Phase 4: User Decision
├─ Select solution approach
├─ Select execution method (Agent/Codex/Auto)
├─ Select code review tool (Skip/Gemini/Codex/Agent)
└─ Route:
├─ Approve → Phase 5
├─ Need More Analysis → Return to Phase 2
└─ Cancel → Save session
Phase 5: Plan Generation & Execution Handoff
├─ Generate plan.json + .task/*.json (via @cli-lite-planning-agent, two-layer output)
├─ Build executionContext with user selections and taskFiles
└─ Execute via workflow-lite-execute| Agent | Responsibility |
|---|---|
| Orchestrator | Session management, ACE context, user decisions, phase transitions, executionContext assembly |
| @cli-discuss-agent | Multi-CLI execution (Gemini/Codex/Claude), cross-verification, solution synthesis, synthesis.json output |
| @cli-lite-planning-agent | Task decomposition, two-layer output: plan.json (overview with task_ids[]) + .task/*.json (task files) |
Session Initialization:
const sessionId = `MCP-${taskSlug}-${date}`
const sessionFolder = `.workflow/.multi-cli-plan/${sessionId}`
Bash(`mkdir -p ${sessionFolder}/rounds`)ACE Context Queries:
const aceQueries = [
`Project architecture related to ${keywords}`,
`Existing implementations of ${keywords[0]}`,
`Code patterns for ${keywords} features`,
`Integration points for ${keywords[0]}`
]
// Execute via mcp__ace-tool__search_contextContext Package (passed to agent):
relevant_files[] - Files identified by ACEdetected_patterns[] - Code patterns foundarchitecture_insights - Structure understandingCore Principle: Orchestrator only delegates and reads output — NO direct CLI execution. CLI calls MUST use Bash with run_in_background: true, wait for hook callback, do NOT use TaskOutput polling.
Agent Invocation:
Agent({
subagent_type: "cli-discuss-agent",
run_in_background: false,
description: `Discussion round ${currentRound}`,
prompt: `
## Input Context
- task_description: ${taskDescription}
- round_number: ${currentRound}
- session: { id: "${sessionId}", folder: "${sessionFolder}" }
- ace_context: ${JSON.stringify(contextPackage)}
- previous_rounds: ${JSON.stringify(analysisResults)}
- user_feedback: ${userFeedback || 'None'}
- cli_config: { tools: ["gemini", "codex"], mode: "parallel", fallback_chain: ["gemini", "codex", "claude"] }
## Execution Process
1. Parse input context (handle JSON strings)
2. Check if ACE supplementary search needed
3. Build CLI prompts with context
4. Execute CLIs (parallel or serial per cli_config.mode)
5. Parse CLI outputs, handle failures with fallback
6. Perform cross-verification between CLI results
7. Synthesize solutions, calculate scores
8. Calculate convergence, generate clarification questions
9. Write synthesis.json
## Output
Write: ${sessionFolder}/rounds/${currentRound}/synthesis.json
## Completion Checklist
- [ ] All configured CLI tools executed (or fallback triggered)
- [ ] Cross-verification completed with agreements/disagreements
- [ ] 2-3 solutions generated with file:line references
- [ ] Convergence score calculated (0.0-1.0)
- [ ] synthesis.json written with all Primary Fields
`
})Read Agent Output:
const synthesis = JSON.parse(Read(`${sessionFolder}/rounds/${round}/synthesis.json`))
// Access top-level fields: solutions, convergence, cross_verification, clarification_questionsConvergence Decision:
if (synthesis.convergence.recommendation === 'converged') {
// Proceed to Phase 3
} else if (synthesis.convergence.recommendation === 'user_input_needed') {
// Collect user feedback, return to Phase 2
} else {
// Continue to next round if new_insights && round < maxRounds
}Display solutions from synthesis.solutions[] showing: name, source CLIs, effort/risk, pros/cons, affected files (file:line). Also show cross-verification agreements/disagreements count.
AskUserQuestion({
questions: [
{
question: "Which solution approach?",
header: "Solution",
multiSelect: false,
options: solutions.map((s, i) => ({
label: `Option ${i+1}: ${s.name}`,
description: `${s.effort} effort, ${s.risk} risk`
})).concat([
{ label: "Need More Analysis", description: "Return to Phase 2" }
])
},
{
question: "Execution method:",
header: "Execution",
multiSelect: false,
options: [
{ label: "Agent", description: "@code-developer agent" },
{ label: "Codex", description: "codex CLI tool" },
{ label: "Auto", description: "Auto-select based on complexity" }
]
},
{
question: "Code review after execution?",
header: "Review",
multiSelect: false,
options: [
{ label: "Skip", description: "No review" },
{ label: "Gemini Review", description: "Gemini CLI tool" },
{ label: "Codex Review", description: "Codex CLI: prompt-based code quality review (--mode analysis)" },
{ label: "Agent Review", description: "Current agent review" }
]
}
]
})Routing:
TodoWrite Update (Phase 4 Decision):
const executionLabel = userSelection.execution_method // "Agent" / "Codex" / "Auto"
TodoWrite({ todos: [
{ content: "Phase 1: Context Gathering", status: "completed", activeForm: "Gathering context" },
{ content: "Phase 2: Multi-CLI Discussion", status: "completed", activeForm: "Running discussion" },
{ content: "Phase 3: Present Options", status: "completed", activeForm: "Presenting options" },
{ content: `Phase 4: User Decision [${executionLabel}]`, status: "completed", activeForm: "Decision recorded" },
{ content: `Phase 5: Plan Generation [${executionLabel}]`, status: "in_progress", activeForm: `Generating plan [${executionLabel}]` }
]})Step 1: Build Context-Package (Orchestrator responsibility):
const contextPackage = {
solution: {
name: selectedSolution.name,
source_cli: selectedSolution.source_cli,
feasibility: selectedSolution.feasibility,
effort: selectedSolution.effort,
risk: selectedSolution.risk,
summary: selectedSolution.summary
},
implementation_plan: selectedSolution.implementation_plan,
dependencies: selectedSolution.dependencies || { internal: [], external: [] },
technical_concerns: selectedSolution.technical_concerns || [],
consensus: {
agreements: synthesis.cross_verification.agreements,
resolved_conflicts: synthesis.cross_verification.resolution
},
constraints: userConstraints || [],
task_description: taskDescription,
session_id: sessionId
}
Write(`${sessionFolder}/context-package.json`, JSON.stringify(contextPackage, null, 2))Step 2: Invoke Planning Agent:
Agent({
subagent_type: "cli-lite-planning-agent",
run_in_background: false,
description: "Generate implementation plan",
prompt: `
## Schema Reference
Execute: cat ~/.ccw/workflows/cli-templates/schemas/plan-overview-base-schema.json
Execute: cat ~/.ccw/workflows/cli-templates/schemas/task-schema.json
## Output Format: Two-Layer Structure
- plan.json: Overview with task_ids[] referencing .task/ files (NO tasks[] array)
- .task/TASK-*.json: Independent task files following task-schema.json
plan.json required: summary, approach, task_ids, task_count, _metadata (with plan_type)
Task files required: id, title, description, depends_on, convergence (with criteria[])
Task fields: files[].change (not modification_points), convergence.criteria (not acceptance), test (not verification)
## Context-Package (from orchestrator)
${JSON.stringify(contextPackage, null, 2)}
## Execution Process
1. Read plan-overview-base-schema.json + task-schema.json for output structure
2. Read project-tech.json and specs/*.md
3. Parse context-package fields:
- solution: name, feasibility, summary
- implementation_plan: tasks[], execution_flow, milestones
- dependencies: internal[], external[]
- technical_concerns: risks/blockers
- consensus: agreements, resolved_conflicts
- constraints: user requirements
4. Use implementation_plan.tasks[] as task foundation
5. Preserve task dependencies (depends_on) and execution_flow
6. Expand tasks with convergence.criteria (testable completion conditions)
7. Create .task/ directory and write individual TASK-*.json files
8. Generate plan.json with task_ids[] referencing .task/ files
## Output
- ${sessionFolder}/plan.json (overview with task_ids[])
- ${sessionFolder}/.task/TASK-*.json (independent task files)
## Completion Checklist
- [ ] plan.json has task_ids[] and task_count (NO embedded tasks[])
- [ ] .task/*.json files preserve task dependencies from implementation_plan
- [ ] Task execution order follows execution_flow
- [ ] Key_points reflected in task descriptions
- [ ] User constraints applied to implementation
- [ ] convergence.criteria are testable
- [ ] plan.json follows plan-overview-base-schema.json
- [ ] Task files follow task-schema.json
`
})Step 3: Build executionContext:
const plan = JSON.parse(Read(`${sessionFolder}/plan.json`))
const taskFiles = plan.task_ids.map(id => `${sessionFolder}/.task/${id}.json`)
// Build executionContext (same structure as lite-plan)
executionContext = {
planObject: plan,
taskFiles: taskFiles, // Paths to .task/*.json files (two-layer format)
explorationsContext: null, // Multi-CLI doesn't use exploration files
explorationAngles: [],
explorationManifest: null,
clarificationContext: null, // Store user feedback from Phase 2 if exists
executionMethod: userSelection.execution_method, // From Phase 4
codeReviewTool: userSelection.code_review_tool, // From Phase 4
originalUserInput: taskDescription,
executorAssignments: null,
session: {
id: sessionId,
folder: sessionFolder,
artifacts: {
explorations: [], // No explorations in multi-CLI workflow
explorations_manifest: null,
plan: `${sessionFolder}/plan.json`,
task_dir: plan.task_ids ? `${sessionFolder}/.task/` : null,
synthesis_rounds: Array.from({length: currentRound}, (_, i) =>
`${sessionFolder}/rounds/${i+1}/synthesis.json`
),
context_package: `${sessionFolder}/context-package.json`
}
}
}Step 4: Hand off to Execution:
Skill({
skill: "workflow-lite-execute",
args: "--in-memory"
})
// executionContext is passed via global variable to workflow-lite-execute (Mode 1: In-Memory Plan){
"round": 1,
"solutions": [{
"name": "Solution Name",
"source_cli": ["gemini", "codex"],
"feasibility": 0.85,
"effort": "low|medium|high",
"risk": "low|medium|high",
"summary": "Brief analysis summary",
"implementation_plan": {
"approach": "High-level technical approach",
"tasks": [
{"id": "T1", "name": "Task", "depends_on": [], "files": [], "key_point": "..."}
],
"execution_flow": "T1 → T2 → T3",
"milestones": ["Checkpoint 1", "Checkpoint 2"]
},
"dependencies": {"internal": [], "external": []},
"technical_concerns": ["Risk 1", "Blocker 2"]
}],
"convergence": {
"score": 0.85,
"new_insights": false,
"recommendation": "converged|continue|user_input_needed"
},
"cross_verification": {
"agreements": [],
"disagreements": [],
"resolution": "..."
},
"clarification_questions": []
}Initialization (Phase 1 start):
TodoWrite({ todos: [
{ content: "Phase 1: Context Gathering", status: "in_progress", activeForm: "Gathering context" },
{ content: "Phase 2: Multi-CLI Discussion", status: "pending", activeForm: "Running discussion" },
{ content: "Phase 3: Present Options", status: "pending", activeForm: "Presenting options" },
{ content: "Phase 4: User Decision", status: "pending", activeForm: "Awaiting decision" },
{ content: "Phase 5: Plan Generation", status: "pending", activeForm: "Generating plan" }
]}).workflow/.multi-cli-plan/{MCP-task-slug-YYYY-MM-DD}/
├── session-state.json # Session tracking (orchestrator)
├── rounds/
│ ├── 1/synthesis.json # Round 1 analysis (cli-discuss-agent)
│ ├── 2/synthesis.json # Round 2 analysis (cli-discuss-agent)
│ └── .../
├── context-package.json # Extracted context for planning (orchestrator)
├── plan.json # Plan overview with task_ids[] (NO embedded tasks[])
└── .task/ # Independent task files
├── TASK-001.json # Task file following task-schema.json
├── TASK-002.json
└── ...| Error | Resolution |
|---|---|
| ACE search fails | Fall back to Glob/Grep for file discovery |
| Agent fails | Retry once, then present partial results |
| CLI timeout (in agent) | Agent uses fallback: gemini → codex → claude |
| No convergence | Present best options, flag uncertainty |
| synthesis.json parse error | Request agent retry |
| User cancels | Save session for later resumption |
| Flag | Default | Description |
|---|---|---|
--max-rounds | 3 | Maximum discussion rounds |
--tools | gemini,codex | CLI tools for analysis |
--mode | parallel | Execution mode: parallel or serial |
--auto-execute | false | Auto-execute after approval |
© 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 .claude/skills/workflow-multi-cli-plan of catlog22/Claude-Code-Workflow.
Open the folder on GitHubat commit 07491b0
Workflow Multi CLI Plan 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 |
|---|---|---|---|---|---|---|
| Workflow Multi CLI Plan this skillcatlog22/Claude-Code-Workflow | 2.1k | — | ~3.9k | Automated safety check: Notes | MIT | |
| ccc Semantic Code Searchcocoindex-io/cocoindex-code | 2.7k | — | ~938 | Automated safety check: Pass | Apache-2.0 | |
| Context Engineeringabashev/vfs-s3 | 106 | 9 repos | ~2.6k | Automated safety check: Notes | Apache-2.0 | |
| Repomix Codebase Packeryamadashy/repomix | 29k | — | ~1.3k | Automated safety check: Notes | MIT | |
| Codebase Handbook BuilderRuhan-Wang/Harness_Handbook | 332 | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| CodemapJordanCoin/codemap | 704 | — | ~1.8k | Automated safety check: Pass | MIT |
cocoindex-io/cocoindex-code
Semantic code search and index management with the ccc CLI: the agent initializes, indexes and queries the project by concept, filtering by language or path.
abashev/vfs-s3
Optimizes agent context setup. An agent skill from abashev/vfs-s3.
yamadashy/repomix
Packs a local directory or remote GitHub repository into one AI-friendly file with Repomix, then searches it to explore structure, find patterns and count tokens.
Ruhan-Wang/Harness_Handbook
Generates, refreshes, validates and uses a compact handbook that maps where a change touches in a repository, using the active Codex session and no external LLM API.
JordanCoin/codemap
Gives an agent a quick map of a codebase's structure, dependencies, changes and handoffs, and tunes per-project config so the output stays code-first.
sopaco/deepwiki-rs
A skill your agent uses when an agent needs source code from the local repomix index under .terrain/agent/repomix.md (not committed; regenerate via Terrain scan).
catlog22/Claude-Code-Workflow
Generate or convert Claude Code prompt files — command orchestrators, skill files, agent role definitions, or style conversion of existing files.
catlog22/Claude-Code-Workflow
CCW command help system. An agent skill from catlog22/Claude-Code-Workflow.
catlog22/Claude-Code-Workflow
Deep collaborative analysis team skill. 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.
Categories
Multi-CLI collaborative planning with codebase context gathering, iterative cross-verification, and execution handoff. Workflow Multi CLI Plan is an agent skill from catlog22/Claude-Code-Workflow. Multi-CLI collaborative planning with codebase context gathering, iterative cross-verification, and execution handoff.
Workflow Multi CLI Plan fits situations like: tasks that involve Codebase knowledge for agents.
Run `npx skills add catlog22/Claude-Code-Workflow --skill workflow-multi-cli-plan -a claude-code`. Or copy the skill folder (.claude/skills/workflow-multi-cli-plan in catlog22/Claude-Code-Workflow) into .claude/skills/workflow-multi-cli-plan in your project. Claude Code loads it when a task matches its description.
Run `npx skills add catlog22/Claude-Code-Workflow --skill workflow-multi-cli-plan -a codex`. Or copy the skill folder (.claude/skills/workflow-multi-cli-plan in catlog22/Claude-Code-Workflow) into .agents/skills/workflow-multi-cli-plan 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 workflow-multi-cli-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/workflow-multi-cli-plan, .gemini/skills/workflow-multi-cli-plan, .github/skills/workflow-multi-cli-plan and .opencode/skills/workflow-multi-cli-plan in your project.
SKILL.md names no scripts, command-line tools or credentials: Workflow Multi CLI Plan is instructions for the agent only. Its frontmatter pre-approves these tools: Skill, Agent, AskUserQuestion, TodoWrite, Read, Write, Edit, Bash, Glob, Grep.
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.
Workflow Multi CLI Plan is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.9k tokens (SKILL.md is roughly 15k 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 Workflow Multi CLI Plan: ccc Semantic Code Search (cocoindex-io/cocoindex-code, 2.7k stars), Context Engineering (abashev/vfs-s3, 106 stars), Repomix Codebase Packer (yamadashy/repomix, 29k stars) and Codebase Handbook Builder (Ruhan-Wang/Harness_Handbook, 332 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.