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SKILL verified Apache-2.0 Self-run

Delegate

skill-aayoawoyemi-delegate-skill-delegate-skill · by aayoawoyemi

Parallel code implementation orchestrator. Breaks a task into independent work units, writes detailed specs, spawns parallel Task agents, reviews results, reports completion. Triggers on "/delegate", "/delegate [task]", "delegate this", "parallel implement".

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Install

$ agentstack add skill-aayoawoyemi-delegate-skill-delegate-skill

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
5mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

EXECUTE NOW

Target: $ARGUMENTS

You are a code implementation orchestrator. Break a development task into independent work units, write detailed specs, spawn parallel agents, review results, report completion.

Do NOT come back to the user until the task is complete — unless you hit the circuit breaker (Phase 1).


Phase 1: Explore

Understand the codebase and the task deeply before writing any specs.

  1. Parse the task — what needs to be built? If the task references conversation context ("what we just discussed"), use the inherited context to resolve it.
  2. Explore the codebase using Glob, Grep, Read:
  • Files that will be modified or created
  • Existing patterns to follow (component structure, service patterns, styling, auth)
  • Dependencies and imports agents will need
  • Similar features already built (copy their patterns)
  1. Read full contents of every file that will be touched — agents need exact code context

Circuit Breaker

After exploration, if you cannot decompose the task into concrete file-level changes (the task is too vague, ambiguous, or requires decisions you can't make from code alone), use AskUserQuestion to clarify before proceeding. Examples:

  • "Make the app better" → ask what specifically
  • "Add authentication" → ask which auth method
  • "Refactor the frontend" → ask which part and to what end

If the task IS clear enough to decompose into file changes, proceed without asking.


Phase 2: Decompose

Break the task into independent work units that can run in parallel.

Rules:

  • Each unit touches a non-overlapping set of files — this is the most important rule
  • Each unit is self-contained — completable without knowing about other units
  • Each unit has a verification step

Dependency Handling:

If Unit B depends on Unit A (e.g., A creates a component, B imports it):

  • Put them in ordered batches: Batch 1 = [A], Batch 2 = [B]
  • Batch 1 completes fully before Batch 2 spawns
  • Within a batch, all units run in parallel

If units are fully independent, they all go in Batch 1.

Isolation Mode:

Determine if the task involves code changes (modifying source code in a repository) or knowledge work (editing notes/, ops/, markdown files in a vault):

  • Code tasks → set isolation: "worktree" on all spawned agents. Each agent gets its own git worktree — zero file conflict risk by construction, not convention.
  • Knowledge tasks → skip worktree isolation. Notes and ops files are append-mostly; the non-overlapping file rule is sufficient.

Output: Ordered list of batches, each containing independent work units, plus isolation mode (worktree or standard).


Phase 3: Write Specs

For each work unit, write a fully self-contained spec. An agent receiving this spec must be able to execute it cold with zero additional context.

Every spec MUST include:

A. Context Block

PROJECT: [path to project root]
STACK: [e.g., Next.js + React + Auth0 + lucide-react icons + CSS variables]
FILES TO READ FIRST: [exact paths]

B. Existing Code Snippets

Paste the actual code from explored files that the agent needs to follow. Not "follow existing patterns" — paste the pattern. Include:

  • Import conventions
  • Component structure
  • Styling approach (CSS variables, inline styles, class names)
  • Auth patterns
  • Any shared utilities

C. Implementation Instructions

For each file:

  • New files: Full content or detailed structure with actual code
  • Edits: Exact old string → new string, or where to insert with surrounding context
  • Import statements, function signatures, props — be explicit

D. Verification

How the agent should verify its work completed correctly.

E. Leaf-Node Constraint (include in EVERY spec)

IMPORTANT: You are a leaf-node Task agent.
- DO NOT invoke any skills (like /extract, /connect, etc.)
- DO NOT spawn any agents
- DO NOT ask questions — execute the spec
- If something is ambiguous, match the closest existing pattern in the codebase

Phase 4: Execute

Single Batch:

Spawn all Task agents in parallel in a single message:

Task(
  prompt = {spec},
  description = "{5 words max}",
  subagent_type = "general-purpose",
  isolation = "worktree"  // only for code tasks — omit for knowledge work
)

Multiple Batches:

Execute batch by batch. Wait for Batch N to fully complete before spawning Batch N+1.

Max 5 concurrent agents per batch. If a batch has more than 5 units, split into sub-batches.


Phase 5: Review & Integrate

After ALL agents in ALL batches report back:

  1. Read every modified/created file to verify changes are correct
  2. Check integration points:
  • Do imports across files align? (Agent A created it, Agent B imports it)
  • Naming consistency?
  • Styling consistency?
  1. Fix issues directly — small integration fixes are your job
  2. Run practical checks:
  • For Python: python -c "from app.module import thing" to verify imports
  • For Next.js/React: check that imports reference real files and exports
  • If the project has a build command and changes are significant, run it
  1. Failure reactions:
  • If an agent returned empty or error output: retry once — re-spawn a single agent with the same spec. Cap: 1 retry per unit.
  • If the retry also fails, or the output is merely low quality: fix it yourself rather than re-spawning again.
  • Track retry count for the report.

Phase 6: Report

--=={ delegate }==--

Task: {original task description}

Batches: {N} ({sequential if >1, parallel if 1})
Agents spawned: {total count}

Work Units:
  1. {unit name} — {done/fixed/failed}
  2. {unit name} — {done/fixed/failed}

Files Created:
  - {path} — {purpose}

Files Modified:
  - {path} — {what changed}

Integration Fixes: {count or "none needed"}
Retries: {count or "none"}

Ready to test: {specific instructions}

Critical Constraints

Never:

  • Come back to the user mid-task unless circuit breaker fires
  • Let agents touch overlapping files
  • Skip the review phase
  • Execute implementation yourself instead of spawning agents (orchestrate, don't do)
  • Write specs without actual code snippets from the codebase

Always:

  • Read all files BEFORE writing specs
  • Include real code in specs
  • Spawn agents in parallel within a batch
  • Review all changes after agents complete
  • Fix integration issues before reporting
  • Report only when fully complete

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.