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Agent Skill · 研究检索

ln-300-task-coordinator(ln 300 任务协调员)

ln-300-task-coordinator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ln-300-task-coordinator 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 17,288。

总安装 6,689周安装 268GitHub Stars 437下载 2,165核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ln-300-task-coordinator(ln 300 任务协调员)
来源仓库:https://github.com/levnikolaevich/claude-code-skills
仓库路径:skills/ln-300-task-coordinator
安装命令:
npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-300-task-coordinator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-300-task-coordinator

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

ln-300-task-coordinator 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 核验具体用法。

安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/ln-300-task-coordinator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-3…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ln-300-task-coordinator 怎么安装?

在终端执行 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-300-task-co…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ln-300-task-coordinator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ln-300-task-coordinator 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-300-task-coordinator;npx skills add levnikolaevich/claude-code-skills --skill "ln-300-task-coordinator" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

ln-300-task-coordinator 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

ln-300-task-coordinator 用的人多吗?

公开数据是累计安装 6,689 次,近一周安装 268 次,下载 2,165 次,GitHub 437 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ln-300-task-coordinator 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ln-300-task-coordinator

ln 300 任务协调员 · 本页

6,689437执行命令MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Paths: File paths (shared/, references/, ../ln-*) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root.

Task Coordinator

Type: L2 Domain Coordinator Category: 3XX Planning

Runtime-backed task planning coordinator. The runtime owns readiness gating, pause/resume, and worker result tracking.

MANDATORY READ: Load shared/references/coordinator_runtime_contract.md, shared/references/task_planning_runtime_contract.md, shared/references/coordinator_summary_contract.md, and shared/references/task_plan_worker_runtime_contract.md MANDATORY READ: Load shared/references/environment_state_contract.md, shared/references/storage_mode_detection.md, shared/references/problem_solving.md, and shared/references/creation_quality_checklist.md MANDATORY READ: Load shared/references/mcp_tool_preferences.md, shared/references/mcp_integration_patterns.md, and shared/references/agent_delegation_pattern.md when Phase 3 external validation is triggered

Purpose

  • resolve Story context once
  • build an ideal implementation task plan before checking existing tasks
  • run a deterministic readiness gate
  • detect CREATE, ADD, or REPLAN
  • delegate to standalone workers

Inputs

ParameterRequiredDescription
storyIdYesStory to plan
autoApproveNoIf false, runtime may pause for readiness approval

Runtime

Runtime family: task-planning-runtime

Identifier:

  • story-{storyId}

Phases:

  1. PHASE_0_CONFIG
  2. PHASE_1_DISCOVERY
  3. PHASE_2_DECOMPOSE
  4. PHASE_3_READINESS_GATE
  5. PHASE_4_MODE_DETECTION
  6. PHASE_5_DELEGATE
  7. PHASE_6_VERIFY
  8. PHASE_7_SELF_CHECK

Terminal phases:

  • DONE
  • PAUSED

Coordinator stage artifact:

  • write summary_kind=pipeline-stage after verification
  • ln-1000 consumes this artifact as the Stage 0 completion signal

Phase Map

Phase 1: Discovery

Resolve Story and collect only the inputs required for task planning:

  • Story AC
  • Technical Notes
  • Context
  • project architecture and tech stack
  • task provider

Do NOT load existing tasks here. Existing tasks load in Phase 4 only.

  • For Stories that modify existing code in supported languages, build graph context once:

- index_project(path=project_root) - analyze_architecture(path=project_root, verbosity="minimal") - find_symbols + inspect_symbol for named components from Story AC or Technical Notes, but only after narrowing path where possible; if symbol discovery is truncated, refine to name + file or workspace_qualified_name before planning from it

  • Use graph context to confirm real affected modules and entrypoints before decomposition

Checkpoint payload:

  • discovery_ready

Phase 2: Decompose

Build the ideal task plan from ACs only. Do not read or reference existing tasks.

Order of operations:

  1. Build AC-to-Scenario traceability table with these columns: AC | Actor | (1) Trigger | (2) Entry Point | (3) Discovery | (4) Usage Context | (5) Outcome
  2. Scan Entry Point, Discovery, and Usage Context cells for buildable artifacts
  3. Group buildable artifacts by architectural layer using segment boundaries:

- Foundation: the internal logic, data model, or service that does the work (what Entry Point calls into) - Invocation: the Entry Point itself — the named mechanism the actor uses - Knowledge: the Usage Context — what the actor needs to correctly invoke the mechanism - Wiring: Discovery + integration — how the system finds/loads the mechanism and connects components

  1. Each layer group becomes at least one task. A single task MUST NOT span more than one layer unless trivially small.
  2. When graph context exists, use it to:

- split tasks by actual modules or symbol ownership, not guessed file groups - keep dependency order aligned with real callers, framework entrypoints, and public APIs - enrich Affected Components with real modules/symbols returned by graph analysis

  1. Verify foundation-first ordering and 1-8 task count
  2. Save the traceability table and layer grouping to .hex-skills/task-planning/{identifier}_traceability.md

Rules:

  • implementation tasks only
  • 1-8 tasks
  • no tests or refactoring tasks here
  • preserve foundation-first order
  • assign meaningful verification intent
  • infrastructure-only tasks do not satisfy ACs that require something to *use* that infrastructure
  • an invocation-layer task does not satisfy ACs that require the actor to *know how* to use that mechanism — that is a knowledge-layer artifact
  • see #17b, #17c, #17d in creation_quality_checklist.md

Checkpoint payload:

  • ideal_plan_summary
  • traceability_table_path

Phase 3: Readiness Gate

Score the plan before delegation.

Step 1: Self-score

Scoring policy:

  • 6-7 -> continue
  • 4-5 -> PAUSED for approval or improvement
  • <4 -> blocked until plan is corrected

Self-check: verify each layer (Foundation, Invocation, Knowledge, Wiring) has at least one task when the traceability table contains buildable artifacts in the corresponding segments.

Step 2: Conditional external traceability validation

Run this step only when at least one trigger is true:

  • readiness score is 4-5
  • mode looks ambiguous (ADD vs REPLAN)
  • AC-to-task coverage is incomplete
  • task boundaries or layer ownership still conflict after self-score

If triggered:

  1. Run agent health check: node shared/agents/agent_runner.mjs --health-check --json
  2. If advisor agent available: a. Build validation prompt from shared/agents/prompt_templates/traceability_validator.md b. Fill placeholders with Phase 1 discovery and Phase 2 output c. Save filled prompt to .hex-skills/task-planning/{identifier}_traceability_prompt.md d. Launch agent via agent_runner.mjs: node shared/agents/agent_runner.mjs \ --agent {advisor_agent} \ --prompt-file.hex-skills/task-planning/{identifier}_traceability_prompt.md \ --output-file.hex-skills/task-planning/{identifier}_traceability_result.json \ --cwd {project_dir} e. Parse result JSON for gaps f. For each MISSING gap: readiness_score -= 1 g. For each BUNDLED gap: readiness_score -= 0.5 h. If MISSING gaps found: re-enter Phase 2. Max 1 re-decomposition.
  3. If no agent available: log and keep the local score with degraded confidence.

If not triggered:

  • set traceability_validation = self_check_only
  • advance without external validation

Checkpoint payload:

  • readiness_score
  • readiness_findings
  • traceability_validation — one of: agent_validated, self_check_only, redecomposed

Phase 4: Mode Detection

Detect:

  • CREATE
  • ADD
  • REPLAN

Pause when mode is ambiguous.

Checkpoint payload:

  • mode_detection

Phase 5: Delegate

Single mutation handoff. Delegate to exactly one worker:

  • ln-301-task-creator
  • ln-302-task-replanner

Managed delegation sequence:

  1. Compute childRunId = {parent_run_id}--{worker}--{storyId}.
  2. Compute childSummaryArtifactPath =.hex-skills/runtime-artifacts/runs/{parent_run_id}/task-plan/{worker}--{storyId}.json.
  3. Materialize child manifest at .hex-skills/task-planning/{worker}--{storyId}_manifest.json.
  4. Start task-plan-worker-runtime with both --run-id and --summary-artifact-path.
  5. Checkpoint child_run metadata before invoking the worker.
  6. Invoke the worker through Skill tool with both transport inputs.
  7. Read only the final task-plan artifact and record it through runtime record-plan.

Coordinator context to pass to workers:

  • idealPlan: the full ideal plan from Phase 2
  • traceabilityTablePath: path to materialized traceability table
  • discoveryContext: Phase 1 findings
  • In ADD mode: specify which tasks to create

Phase 6: Verify

Verify the worker result and the resulting task set only. Do not reopen decomposition unless verification proves the worker output is invalid.

Template compliance gate: Fetch each created Task via get_issue. Run validateTemplateCompliance(description, 'task') from planning-runtime/lib/template-compliance.mjs. All tasks must pass (7 sections in order). Record template_compliance_passed in state. Guard blocks SELF_CHECK without it.

Checkpoint payload:

  • verification_summary
  • final_result
  • template_compliance_passed

After verification succeeds, write a Stage 0 coordinator artifact with:

  • stage=0
  • story_id
  • status=completed
  • final_result
  • story_status
  • readiness_score
  • warnings

Phase 7: Self-Check

Confirm:

  • phase coverage
  • readiness gate was respected
  • worker result was recorded
  • verification completed
  • Stage 0 coordinator artifact was recorded

Checkpoint payload:

  • pass
  • final_result

Pending Decisions

Use runtime PAUSED + pending_decision for:

  • ambiguous ADD vs REPLAN
  • readiness approval for score 4-5
  • missing critical Story context

Worker Contract

Workers:

  • do not know the coordinator
  • do not read runtime state
  • remain standalone
  • managed runs require both runId and summaryArtifactPath
  • return the shared task-plan summary envelope and write the artifact before terminal outcome

Expected summary kind:

  • task-plan

Worker Invocation (MANDATORY)

PhaseWorkerContext
5ln-301-task-creatorCREATE or ADD path
5ln-302-task-replannerREPLAN path
node shared/scripts/task-plan-worker-runtime/cli.mjs start --skill {worker} --story {storyId} --manifest-file .hex-skills/task-planning/{worker}--{storyId}_manifest.json --run-id {childRunId} --summary-artifact-path {childSummaryArtifactPath}
node shared/scripts/task-planning-runtime/cli.mjs checkpoint --story {storyId} --phase PHASE_5_DELEGATE --payload '{"child_run":{"worker":"{worker}","run_id":"{childRunId}","summary_artifact_path":"{childSummaryArtifactPath}"}}'
Skill(skill: "{worker}", args: "{storyId} --ideal-plan {idealPlanJSON} --traceability {tablePath} --discovery {discoveryJSON} --run-id {childRunId} --summary-artifact-path {childSummaryArtifactPath}")
Read {childSummaryArtifactPath}
node shared/scripts/task-planning-runtime/cli.mjs record-plan --story {storyId} --payload '{...task-plan summary...}'

TodoWrite format (mandatory)

- Phase 1: Discover Story context (pending)
- Phase 2: Build ideal task plan (pending)
- Phase 3: Run readiness gate (local score first, external validation only if triggered) (pending)
- Phase 4: Detect mode (pending)
- Phase 5: Start child runtime, checkpoint child metadata, and perform the single worker handoff (pending)
- Phase 6: Verify worker result (pending)
- Phase 7: Self-check (pending)

Critical Rules

  • Build the ideal plan before looking at existing tasks.
  • Readiness gate is the only source of delegation readiness.
  • Do not create test or refactoring tasks in this skill.
  • Do not keep approval state in chat-only form.
  • Consume worker summaries, not free-text worker prose.
  • If Story affects existing code and hex-graph is available, do one graph discovery pass before decomposition.
  • Use graph output to reduce planning ambiguity; do not invent affected components when symbol or module evidence is available.

Definition of Done

  • Runtime started with Story-scoped identifier
  • Discovery checkpointed
  • Ideal plan checkpointed
  • Readiness gate checkpointed
  • Mode detection checkpointed
  • Child task-plan runtime started with deterministic runId
  • Child run metadata checkpointed before delegation
  • Task-plan worker summary recorded
  • Verification checkpointed
  • Template compliance passed for all created Tasks
  • Final result recorded
  • Self-check passed

Meta-Analysis

MANDATORY READ: Load shared/references/meta_analysis_protocol.md

Skill type: planning-coordinator. Run after all phases complete. Output to chat using the protocol format.


Version: 4.0.0 Last Updated: 2026-02-03

平台分布

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27.57%
按下载量换算597

Gemini CLI

22.27%
按下载量换算482

Codex

17.25%
按下载量换算373

OpenCode

13.33%
按下载量换算289

Antigravity

8.84%
按下载量换算191

windsurf

3.2%
按下载量换算69

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通过

Socket

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Snyk

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权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-300-task-coordinator;npx skills add levnikolaevich/claude-code-skills --skill "ln-300-task-coordinator" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

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