Messages Ops
affaan-m/ECC
Evidence-first live messaging workflow for ECC. An agent skill from affaan-m/ECC.
Batch all related operations into single messages for maximum parallelism and performance.
$ npx skills add MadAppGang/claude-code --skill batching-patterns -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MadAppGang/claude-code batching-patterns --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/MadAppGang/claude-code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/multimodel/skills/batching-patterns .claude/skills/batching-patterns && 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 "batching-patterns" agent skill from https://github.com/MadAppGang/claude-code/tree/main/plugins/multimodel/skills/batching-patterns into .claude/skills/batching-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batching-patterns", 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/MadAppGang/claude-code/tree/main/plugins/multimodel/skills/batching-patternsType 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 MadAppGang/claude-code --skill batching-patterns -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MadAppGang/claude-code batching-patterns --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MadAppGang/claude-code.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/multimodel/skills/batching-patterns .agents/skills/batching-patterns && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "batching-patterns" agent skill from https://github.com/MadAppGang/claude-code/tree/main/plugins/multimodel/skills/batching-patterns into .agents/skills/batching-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batching-patterns", 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 MadAppGang/claude-code --skill batching-patterns -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MadAppGang/claude-code batching-patterns --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MadAppGang/claude-code.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/multimodel/skills/batching-patterns .cursor/skills/batching-patterns && 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 "batching-patterns" agent skill from https://github.com/MadAppGang/claude-code/tree/main/plugins/multimodel/skills/batching-patterns into .cursor/skills/batching-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batching-patterns", 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/MadAppGang/claude-code.git --path plugins/multimodel/skills/batching-patterns--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 MadAppGang/claude-code --skill batching-patterns -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MadAppGang/claude-code batching-patterns --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MadAppGang/claude-code.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/multimodel/skills/batching-patterns .gemini/skills/batching-patterns && 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 "batching-patterns" agent skill from https://github.com/MadAppGang/claude-code/tree/main/plugins/multimodel/skills/batching-patterns into .gemini/skills/batching-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batching-patterns", 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 MadAppGang/claude-code batching-patternsInstalls 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 MadAppGang/claude-code --skill batching-patterns -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MadAppGang/claude-code.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/multimodel/skills/batching-patterns .github/skills/batching-patterns && 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 "batching-patterns" agent skill from https://github.com/MadAppGang/claude-code/tree/main/plugins/multimodel/skills/batching-patterns into .github/skills/batching-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batching-patterns", 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 MadAppGang/claude-code --skill batching-patterns -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MadAppGang/claude-code batching-patterns --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MadAppGang/claude-code.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/multimodel/skills/batching-patterns .opencode/skills/batching-patterns && 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 "batching-patterns" agent skill from https://github.com/MadAppGang/claude-code/tree/main/plugins/multimodel/skills/batching-patterns into .opencode/skills/batching-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batching-patterns", 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.
batching-patternsBatch all related operations into single messages for maximum parallelism and performance.
Batching Patterns is an agent skill from MadAppGang/claude-code. Batch all related operations into single messages for maximum parallelism and performance. Use when launching multiple agents, reading multiple files, running parallel searches, optimizing workflow speed, or avoiding sequential execution bottlenecks. Trigger keywords - "batching", "parallel", "single message", "golden rule", "concurrent", "performance", "sequential bottleneck", "speed optimization".
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: claude code plugins marketplace. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 6097ad4. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
npmFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.
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.
Batching Patterns loads about 3.3k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 709 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 found no risky patterns in SKILL.md.
Automated 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 MadAppGang/claude-code at commit 6097ad4, republished under its MIT licence (© MadAppGang). 709 words, ~3,339 tokens.
.claude/skills/batching-patterns/SKILL.md (or your agent's skills folder).Version: 1.0.0 Purpose: The Golden Rule of Claude Code execution -- batch operations for maximum parallelism Status: Production Ready
The Golden Rule of Claude Code performance:
"1 MESSAGE = ALL RELATED OPERATIONS"
Every tool call within a single message executes in parallel (when no dependencies exist). Every separate message introduces a sequential round-trip. This distinction is the difference between a 2-minute workflow and a 10-minute one.
Sequential (5 separate messages):
Message 1: Task(agent-1) → 2 min
Message 2: Task(agent-2) → 2 min (waits for agent-1!)
Message 3-5: ... → 2 min each
Total: ~10 minutes (serial)
Batched (1 message):
Message 1: Task(agent-1) + Task(agent-2) + ... + Task(agent-5)
Total: ~2 minutes (parallel, limited by slowest agent)
Speedup: 5xEach message carries API round-trip overhead. Batching eliminates N-1 round-trips.
Claude Code has a simple execution model:
Same tool type in one message = PARALLEL
Task(A) + Task(B) + Task(C) → All run simultaneously
Different tool types in one message = SEQUENTIAL (often)
TaskCreate(...) + Task(A) + Bash(...) → May run one at a time
Separate messages = ALWAYS SEQUENTIAL
Message 1: Task(A) → completes first
Message 2: Task(B) → starts only after A finishesWhy Same Tool Type Signals Independence:
Multiple calls of the same tool type (all Task, all Read, all Grep) signal independent operations that can run concurrently. Mixing tool types breaks this signal because different types often have implicit ordering requirements.
The most impactful tool to batch -- each agent runs for minutes.
❌ Sequential (3 separate messages):
Message 1: Task(security-reviewer) → 3 min
Message 2: Task(perf-reviewer) → 2 min (waits!)
Message 3: Task(a11y-reviewer) → 2 min (waits!)
Total: ~7 minutes
✅ Batched (1 message):
Task(security-reviewer) + Task(perf-reviewer) + Task(a11y-reviewer)
Total: ~3 minutes (3 agents parallel)
Speedup: 2.3xAgents are independent when they: read same input but don't modify it, write to different output files, perform different analysis, don't need each other's results.
❌ Sequential Reads:
Message 1: Read("src/auth.ts") → round-trip
Message 2: Read("src/middleware.ts") → round-trip
Message 3: Read("src/routes.ts") → round-trip
Total: 3 round-trips
✅ Batched Reads:
Read("src/auth.ts") + Read("src/middleware.ts") + Read("src/routes.ts")
Total: 1 round-trip (3x faster)❌ Sequential Searches:
Message 1: Grep("TODO", path="src/")
Message 2: Grep("FIXME", path="src/")
Message 3: Glob("**/*.test.ts")
✅ Batched Searches:
Grep("TODO") + Grep("FIXME") + Glob("**/*.test.ts")
All parallel in 1 round-trip⚠️ Write/Edit Caution:
❌ Edit("src/auth.ts", change_1) + Edit("src/auth.ts", change_2) ← Conflict!
✅ Edit("src/auth.ts", change_1) + Edit("src/routes.ts", change_2) ← Safe
Rule: Different files = safe to batch. Same file = must be sequential.❌ Individual Calls (5 round-trips):
TaskCreate({ id: "1", title: "Step 1", status: "pending" })
TaskCreate({ id: "2", title: "Step 2", status: "pending" })
...
✅ Single Call (1 round-trip):
TaskCreate({ id: "1", title: "Step 1", status: "pending" })
TaskCreate({ id: "2", title: "Step 2", status: "pending" })
TaskCreate({ id: "3", title: "Step 3", status: "pending" })
# All in same message = parallel execution❌ Sequential Independent Commands:
Message 1: Bash("npm run lint")
Message 2: Bash("npm run typecheck")
Message 3: Bash("npm run test")
✅ Parallel Independent Commands (1 message):
Bash("npm run lint") + Bash("npm run typecheck") + Bash("npm run test")
✅ Dependent Commands Chained (1 Bash call):
Bash("mkdir -p ai-docs && cp template.md ai-docs/plan.md")The canonical batching template from multi-agent-coordination:
Message 1: Preparation (Bash/Write only)
- Create directories, write context files, validate inputs
- NO Task calls, NO Tasks
Message 2: Parallel Execution (Task only)
- ALL agents in SINGLE message, ONLY Task calls
- Same tool type = true parallel execution
Message 3: Consolidation (Task only)
- Consolidation agent reads all output files
Message 4: Present Results
- Show user final consolidated resultsWhy 4 messages: Each depends on the previous (agents need context, consolidation needs agent outputs, presentation needs consolidated result). This is the minimum sequential steps.
❌ Message 1: Task(agent-1) // 2 min
❌ Message 2: Task(agent-2) // 2 min (waits for agent-1!)
❌ Message 3: Task(agent-3) // 2 min (waits for agent-2!)
Total: 6 minutes
✅ Message 1: Task(agent-1) + Task(agent-2) + Task(agent-3) // All parallel!
Total: 2 minutes (3x speedup)❌ Mixed Tools (sequential):
TaskCreate({...}) // Tool type A
Task(security-reviewer) // Tool type B
Bash("echo 'starting'") // Tool type C
Task(perf-reviewer) // Tool type B
✅ Separated (parallel execution):
Message 1: TaskCreate({...}) + Bash("echo 'starting'") // Preparation
Message 2: Task(security-reviewer) + Task(perf-reviewer) // Execution (parallel)❌ 5 separate TaskCreate calls across messages = 5 round-trips
✅ 5 TaskCreate calls in 1 message = 1 round-trip (parallel)❌ 5 separate Read messages = 5 round-trips
✅ 5 Read calls in 1 message = 1 round-trip (5x faster)❌ False Dependencies:
Message 1: Grep("authentication") // Wait...
Message 2: Grep("authorization") // Wait...
Message 3: Glob("**/*.middleware.ts") // Wait...
✅ Recognize Independence:
Message 1: Grep("authentication") + Grep("authorization") + Glob("**/*.middleware.ts")Dependency Detection Checklist:
Before splitting across messages, ask:
If all four are "no," operations are independent -- batch them.
npm install && npm build && npm testCORRECT - Sequential:
Message 1: Task(architect) → writes plan.md
Message 2: Task(developer) → reads plan.md (depends on Message 1)
CORRECT - Chained:
Bash("npm install && npm run build && npm run test")Scenario: 5-Agent Code Review
Sequential: 10 min + 5 round-trips | Batched: 3 min + 1 round-trip | 3.3x
Scenario: 7 Codebase Searches
Sequential: ~21 seconds | Batched: ~3 seconds | 7x
Scenario: 10 File Reads
Sequential: ~20 seconds | Batched: ~2 seconds | 10xSpeedup Formula:
Sequential = N * (execution + round_trip)
Batched = max(executions) + round_trip
Speedup = approximately N (for identical operations)Context Benefits: Fewer messages = less context consumed = more room for useful work.
Do:
Don't:
Message 1: Preparation
Bash("mkdir -p ai-docs/reviews")
Write("ai-docs/review-context.md", code_context)
Message 2: Parallel Execution (5 Task calls)
Task(security-reviewer) → ai-docs/reviews/security.md
Task(performance-reviewer) → ai-docs/reviews/performance.md
Task(accessibility-reviewer) → ai-docs/reviews/accessibility.md
Task(code-quality-reviewer) → ai-docs/reviews/quality.md
Task(architecture-reviewer) → ai-docs/reviews/architecture.md
ALL 5 execute simultaneously
Message 3: Consolidation
Task(review-consolidator) → ai-docs/consolidated-review.md
Message 4: Present Results
Sequential: 5 * 2 min = 10 min | Batched: ~4 min | 2.5x speedupMessage 1: Parallel Searches (7 operations, 1 message)
Grep("authenticate") + Grep("authorize") + Grep("jwt|token")
+ Grep("middleware.*auth") + Glob("**/auth*.ts")
+ Glob("**/middleware/**/*.ts") + Glob("**/*.test.ts")
Message 2: Parallel File Reads (all discovered files)
Read("src/auth/authenticate.ts") + Read("src/auth/authorize.ts")
+ Read("src/middleware/auth.middleware.ts")
+ Read("src/services/token.service.ts")
+ Read("src/routes/auth.routes.ts") + Read("tests/auth/auth.test.ts")
Total: 2 messages, ~5 seconds
Sequential: 13 messages, ~30+ seconds | Speedup: 6x+Message 1 - Preparation (batch reads + setup):
Bash("mkdir -p ai-docs/feature") + Read("src/existing-module.ts")
+ Read("package.json") + Glob("**/*.test.ts")
Message 2 - Planning (depends on Message 1):
Task(architect) → ai-docs/feature/plan.md
Message 3 - Implementation (3 agents parallel, depends on Message 2):
Task(backend-developer) → src/feature/api.ts
Task(frontend-developer) → src/feature/ui.tsx
Task(test-developer) → tests/feature/
Message 4 - Validation (3 checks parallel, depends on Message 3):
Bash("npm run test -- tests/feature/")
Bash("npm run lint -- src/feature/")
Bash("npm run typecheck")
Message 5 - Review (depends on Message 4):
Task(code-reviewer)
Total: 5 messages (minimum for dependency chain)
Without batching: 10+ messages | Speedup: 2-3xParallel agents executing sequentially? Mixed tool types in execution message. Use ONLY Task calls.
File reads arriving one at a time? Each Read in separate message. Batch all Reads into one message.
Conflicting edits? Batched Edit calls targeting same file. Sequence same-file edits, batch different-file edits.
Workflow slower than expected despite batching? Audit dependency chain. Ask at each message boundary: "Does this TRULY depend on the previous one?"
Master batching and every workflow runs at maximum speed.
Inspired By:
© MadAppGang, 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 plugins/multimodel/skills/batching-patterns of MadAppGang/claude-code.
Open the folder on GitHubat commit 6097ad4
Batching Patterns 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 |
|---|---|---|---|---|---|---|
| Batching Patterns this skillMadAppGang/claude-code | 283 | — | ~3.3k | Automated safety check: Pass | MIT | |
| Messages Opsaffaan-m/ECC | 274k | 1 repos | ~724 | Automated safety check: Pass | MIT | |
| Batchasgeirtj/system_prompts_leaks | 69k | — | ~1.3k | Automated safety check: Pass | CC0-1.0 | |
| Batchcodewhale-hq/Codewhale | 41k | — | ~157 | Automated safety check: Pass | MIT | |
| Commit Message Storytellergithub/awesome-copilot | 40k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Agent Messagingdavila7/claude-code-templates | 32k | — | ~807 | Automated safety check: Pass | MIT |
affaan-m/ECC
Evidence-first live messaging workflow for ECC. An agent skill from affaan-m/ECC.
asgeirtj/system_prompts_leaks
Research and plan a large-scale change, then execute it in parallel across 5–30 isolated worktree agents that each open a PR.
codewhale-hq/Codewhale
Break a large, parallelizable goal into bounded work units, coordinate existing agent/worktree machinery, integrate, and verify.
github/awesome-copilot
Analyzes git diffs or staged changes and generates narrative commit messages that explain WHY a change was made, not just what changed — following Conventional Commits format.
davila7/claude-code-templates
Send and receive cryptographically signed messages between AI agents using the Agent Messaging Protocol (AMP).
github/gh-aw
Add new safe-output message types and wire validation/rendering.
MadAppGang/claude-code
Analyzes API documentation from OpenAPI specs to provide TypeScript interfaces, request/response formats, and implementation guidance.
MadAppGang/claude-code
Content brief template and creation methodology for SEO-optimized content.
MadAppGang/claude-code
A skill your agent uses when detecting project technology stack from files/configs/directory structure, auto-loading framework-specific skills, or analyzing multi-stack fullstack projects (e.g…
MadAppGang/claude-code
On-page SEO optimization techniques including keyword density, meta tags, heading structure, and readability.
MadAppGang/claude-code
Techniques for expanding seed keywords and clustering by topic and intent.
MadAppGang/claude-code
SERP analysis techniques for intent classification, feature identification, and competitive intelligence.
Batch all related operations into single messages for maximum parallelism and performance. Batching Patterns is an agent skill from MadAppGang/claude-code. Batch all related operations into single messages for maximum parallelism and performance.
Batching Patterns fits situations like: launching multiple agents; reading multiple files; running parallel searches; optimizing workflow speed.
Run `npx skills add MadAppGang/claude-code --skill batching-patterns -a claude-code`. Or copy the skill folder (plugins/multimodel/skills/batching-patterns in MadAppGang/claude-code) into .claude/skills/batching-patterns in your project. Claude Code loads it when a task matches its description.
Run `npx skills add MadAppGang/claude-code --skill batching-patterns -a codex`. Or copy the skill folder (plugins/multimodel/skills/batching-patterns in MadAppGang/claude-code) into .agents/skills/batching-patterns 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 MadAppGang/claude-code --skill batching-patterns -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/batching-patterns, .gemini/skills/batching-patterns, .github/skills/batching-patterns and .opencode/skills/batching-patterns in your project.
Going by SKILL.md and its folder, Batching Patterns needs the command-line tools its instructions call (npm). Our summary lists: Node.js.
SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Batching Patterns is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k 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 Batching Patterns: Messages Ops (affaan-m/ECC, 274k stars), Batch (asgeirtj/system_prompts_leaks, 69k stars), Batch (codewhale-hq/Codewhale, 41k stars) and Commit Message Storyteller (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
MadAppGang (a GitHub organization) maintains it in MadAppGang/claude-code, which has 283 GitHub stars. The repository holds 69 skills in this directory. The repository was last updated on March 15, 2026.
Source: MadAppGang/claude-code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.