跳到正文
FunCoding

搜索

搜索文档、Skill 和 MCP

dispatching-parallel-agents

Use when facing 2+ independent tasks without a written plan, with no conflicting shared mutable state or sequential dependencies, where parallel delegation beats inline cost; otherwise inline. Planned tasks use subagent-driven-development.

代码质量与审查1.3kskills/dispatching-parallel-agents/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/ganyuanran/aegis/dispatching-parallel-agents/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Dispatching Parallel Agents

Purpose

Use parallel children for two or more ad-hoc, bounded tasks only when their independence is already credible and concurrency is worth the coordination. Parallelism changes elapsed time; it does not relax evidence, ownership, or completion requirements.

Dispatch Gate

Dispatch only when all are true:

  • there are 2+ distinct tasks or evidence questions;
  • one task's result is not needed to define or start another;
  • the tasks do not require overlapping writes or the same mutable resource;
  • a shared root cause is unlikely based on current evidence;
  • each result can be returned with bounded evidence and unresolved unknowns;
  • available concurrency and expected work justify coordination cost.

Keep work inline when decomposition is still exploratory, failures may share a root cause, full-system context is required, or tasks are too small to repay the handoff. A written implementation plan routes to aegis:subagent-driven-development, not this ad-hoc workflow.

Context And Ownership

Choose the live host's context inheritance mode deliberately. Give each child the minimum sufficient instructions and evidence; do not rely on accidental inheritance or assume that context must never be inherited.

Each task packet states:

  • goal and question to resolve;
  • allowed files, systems, and side effects;
  • known facts and evidence locations;
  • constraints, non-goals, and stop condition;
  • expected result shape, including unknowns and verification refs.

Isolated model context does not imply an isolated filesystem, process, Git repository, credential, rate limit, or external service. Prefer read-only investigation. If children may edit, assign disjoint write ownership explicitly. The coordinator owns staging, commits, branches, worktrees, integration, and other Git lifecycle mutations.

Execution

  1. Establish the minimum common baseline and record evidence for the task split.
  2. Dispatch one bounded task per independent domain, within host concurrency limits.
  3. Optionally continue coordinator work that does not race child reads or writes.
  4. On return, check evidence freshness, unknowns, overlapping assumptions, and visible workspace changes.
  5. Synthesize disagreements before acting. If results reveal coupling, stop parallel mutation and return the work to one owner.
  6. For edits, run integrated verification after accepted changes are combined. For read-only work, validate the synthesis against the cited sources.

The coordinator owns the concurrency budget. Children do not delegate recursively unless their packet explicitly permits it. A failed, cancelled, or timed-out child contributes any available partial evidence; otherwise record no result and the unresolved unknowns. Retry only with a materially different packet or serialize the task.

Child output is evidence or a proposal, not a GateDecision, completion authority, or permission for external action.

Common Failure Modes

  • Separate files are treated as proof of separate root causes.
  • Children receive broad conversation history instead of bounded task context.
  • Multiple children edit the same owner or mutate shared services concurrently.
  • A child report is accepted without inspecting evidence or current files.
  • Parallel work is used for a written plan and bypasses its review checkpoints.
  • The coordinator verifies each result alone but never checks the integrated state.

When any of these appears, narrow the packets, serialize the shared portion, or return to the owning debugging or plan workflow.

相似的 Skill

claude-api
anthropics/skills180k

claude-api

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

代码质量与审查

ponytail-review
DietrichGebert/ponytail158k

ponytail-review

Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected code, not only the diff. Each finding is explained in plain English. Use for "review this", "code review", "review the last commit", "review my PR", "is this over-engineered", /ponytail-review.

代码质量与审查

code-review-and-quality
addyosmani/agent-skills103k

code-review-and-quality

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted inline.

代码质量与审查

documentation-and-adrs
addyosmani/agent-skills103k

documentation-and-adrs

Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

代码质量与审查

code-simplification
addyosmani/agent-skills103k

code-simplification

Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

代码质量与审查

understand
Egonex-AI/Understand-Anything86k

understand

Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships

代码质量与审查