Token导航 LogoToken导航

Agent Skill · 研究检索

coordinate-reasoning(坐标推理)

coordinate-reasoning 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。

coordinate-reasoning 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,权限为需要联网;许可证信息还不明确,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 57,864。

总安装 423周安装 18GitHub Stars 12下载 148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
unknown

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:coordinate-reasoning(坐标推理)
来源仓库:https://github.com/pjt222/development-guides
仓库路径:skills/coordinate-reasoning
安装命令:
npx skills add https://github.com/pjt222/development-guides --skill coordinate-reasoning
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/pjt222/development-guides --skill coordinate-reasoning

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。

用于查找、检索和筛选相关信息。适合根据关键词、任务场景或来源线索快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围、维护状态及是否会触发联网或文件读写。coordinate-reasoning 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/coordinate-reasoning

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/pjt222/development-guides --skill coordinate-r…;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

    它需要需要联网,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

coordinate-reasoning 怎么安装?

在终端执行 npx skills add https://github.com/pjt222/development-guides --skill coordinate-reasoning。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

coordinate-reasoning 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。

coordinate-reasoning 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

coordinate-reasoning 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

coordinate-reasoning 用的人多吗?

公开数据是累计安装 423 次,近一周安装 18 次,下载 148 次,GitHub 12 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。

coordinate-reasoning 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。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
coordinate-reasoning

坐标推理 · 本页

42312需要联网未明确通过

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

Coordinate Reasoning

Manage the internal coordination of reasoning processes using stigmergic principles — treating context as an environment where information signals have freshness, decay rates, and interaction rules that produce coherent behavior from simple local protocols.

When to Use

  • During complex tasks where multiple sub-tasks must coordinate (multi-file edits, multi-step refactoring)
  • When context has grown long and information freshness is uncertain
  • After context compression when some information may have been lost
  • When sub-task outputs need to feed into each other cleanly
  • When earlier reasoning results need to be carried forward without degradation
  • Complementing forage-solutions (exploration) and build-coherence (decision) with execution coordination

Inputs

  • Required: Current task decomposition (what sub-tasks exist and how do they relate?)
  • Optional: Known information freshness concerns (e.g., "I read that file 20 messages ago")
  • Optional: Sub-task dependency map (which sub-tasks feed into which?)
  • Optional: Available coordination tools (MEMORY.md, task list, inline notes)

Procedure

Step 1: Classify the Coordination Problem

Different coordination challenges require different signal designs.

AI Coordination Problem Types:
┌─────────────────────┬──────────────────────────────────────────────────┐
│ Type                │ Characteristics                                  │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Foraging            │ Multiple independent searches running in         │
│ (scattered search)  │ parallel or sequence. Coordination need: share   │
│                     │ findings, avoid duplicate work, converge on      │
│                     │ best trail                                       │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Consensus           │ Multiple approaches evaluated, one must be       │
│ (competing paths)   │ selected. Coordination need: independent         │
│                     │ evaluation, unbiased comparison, commitment      │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Construction        │ Building a complex output incrementally (multi-  │
│ (incremental build) │ file edit, long document). Coordination need:    │
│                     │ consistency across parts, progress tracking,     │
│                     │ dependency ordering                              │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Defense             │ Maintaining quality under pressure (tight time,  │
│ (quality under      │ complex requirements). Coordination need:        │
│ pressure)           │ monitoring for errors, rapid correction,         │
│                     │ awareness of degradation                         │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Division of labor   │ Task decomposed into sub-tasks with              │
│ (sub-task mgmt)     │ dependencies. Coordination need: ordering,       │
│                     │ handoff, result integration                      │
└─────────────────────┴──────────────────────────────────────────────────┘

Classify the current task. Most complex tasks are Construction or Division of Labor; most debugging tasks are Foraging; most design decisions are Consensus.

Expected: A clear classification that determines which coordination signals to use. The classification should match how the task actually feels, not how it was described.

On failure: If the task spans multiple types (common for large tasks), identify the dominant type for the current phase. Construction during implementation, Foraging during debugging, Consensus during design. The type can change as the task progresses.

Step 2: Design Context Signals

Treat information in the conversation context as signals with freshness and decay properties.

Information Decay Rate Table:
┌───────────────────────────┬──────────┬──────────────────────────────┐
│ Information Source        │ Decay    │ Refresh Action               │
│                           │ Rate     │                              │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ User's explicit statement │ Slow     │ Re-read if >30 messages ago  │
│ (direct instruction)      │          │ or after compression         │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ File contents read N      │ Moderate │ Re-read if file may have     │
│ messages ago              │          │ been modified, or if >15     │
│                           │          │ messages since reading        │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ Own earlier reasoning     │ Fast     │ Re-derive rather than trust. │
│ (conclusions, plans)      │          │ Earlier reasoning may have   │
│                           │          │ been based on now-stale info  │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ Inferred facts (not       │ Very     │ Verify before relying on.    │
│ directly stated or read)  │ fast     │ Inferences compound error    │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ MEMORY.md / CLAUDE.md     │ Very     │ Loaded at session start,     │
│ (persistent context)      │ slow     │ treat as stable unless user  │
│                           │          │ indicates changes             │
└───────────────────────────┴──────────┴──────────────────────────────┘

Additionally, design inhibition signals — markers for tried-and-failed approaches:

  • After a tool call fails: note the failure mode (prevents retrying the same call)
  • After an approach is abandoned: note why (prevents revisiting without new evidence)
  • After a user correction: note what was wrong (prevents repeating the error)

Expected: A mental model of information freshness across the current context. Identification of which information is fresh and which needs refreshing before reliance.

On failure: If information freshness is hard to assess, default to "re-read before relying on" for anything not verified in the last 5-10 actions. Over-refreshing wastes some effort but prevents stale-information errors.

Step 3: Define Local Protocols

Establish simple rules for how reasoning should proceed at each step, using only locally available information.

Local Protocol Rules:
┌──────────────────────┬────────────────────────────────────────────────┐
│ Protocol             │ Rule                                           │
├──────────────────────┼────────────────────────────────────────────────┤
│ Safety               │ Before using a fact, check: when was it last  │
│                      │ verified? If below freshness threshold,        │
│                      │ re-verify before proceeding                    │
├──────────────────────┼────────────────────────────────────────────────┤
│ Response             │ When the user corrects something, update all  │
│                      │ downstream reasoning that depended on the     │
│                      │ corrected fact. Trace the dependency chain    │
├──────────────────────┼────────────────────────────────────────────────┤
│ Exploitation         │ When a sub-task produces useful output, note  │
│                      │ the output clearly for downstream sub-tasks.  │
│                      │ The note is the trail signal                  │
├──────────────────────┼────────────────────────────────────────────────┤
│ Exploration          │ When stuck on a sub-task for >3 actions       │
│                      │ without progress, check under-explored        │
│                      │ channels: different tools, different files,    │
│                      │ different framing                              │
├──────────────────────┼────────────────────────────────────────────────┤
│ Deposit              │ After completing a sub-task, summarize its    │
│                      │ output in 1-2 sentences for future reference. │
│                      │ This deposit serves the next sub-task          │
├──────────────────────┼────────────────────────────────────────────────┤
│ Inhibition           │ Before trying an approach, check: was this    │
│                      │ already tried and failed? If so, what is      │
│                      │ different now that would change the outcome?  │
└──────────────────────┴────────────────────────────────────────────────┘

These protocols are simple enough to apply at every step without significant overhead.

Expected: A set of lightweight rules that improve coordination quality without slowing execution. The rules should feel helpful, not burdensome.

On failure: If the protocols feel like overhead, reduce to the two most important for the current task type: Safety + Deposit for Construction, Safety + Exploration for Foraging, Safety + Response for tasks with active user feedback.

Step 4: Calibrate Information Freshness

Perform an active audit of information staleness in the current context.

  1. What facts were established more than N messages ago? List them
  2. For each: has it been updated, contradicted, or rendered irrelevant since?
  3. Check for context compression losses: is there information you remember having but can no longer find in the visible context?
  4. Check for drift between early plans and current execution: has the approach changed without updating the plan?
  5. Re-verify the 2-3 most critical facts (the ones that the most downstream reasoning depends on)
Freshness Audit Template:
┌────────────────────────┬──────────┬──────────────┬─────────────────┐
│ Fact                   │ Source   │ Age (approx) │ Status          │
├────────────────────────┼──────────┼──────────────┼─────────────────┤
│                        │          │              │ Fresh / Stale / │
│                        │          │              │ Unknown / Lost  │
└────────────────────────┴──────────┴──────────────┴─────────────────┘

Expected: A concrete inventory of information freshness with stale items identified for refresh. At least one fact re-verified — if nothing needed refreshing, the audit was too shallow or the context is genuinely fresh.

On failure: If the audit reveals significant information loss (multiple facts with "Lost" or "Unknown" status), this is a signal to run heal for a full subsystem assessment. Information loss beyond a threshold means coordination is compromised at the foundation level.

Step 5: Test Emergent Coherence

Verify that the sub-tasks, when combined, produce a coherent whole.

  1. Does each sub-task's output feed cleanly into the next? Or are there gaps, contradictions, or mismatched assumptions?
  2. Are tool calls building toward the goal, or are they repetitive (re-reading the same file, re-running the same search)?
  3. Is the overall direction still aligned with the user's request? Or has incremental drift accumulated into significant misalignment?
  4. Stress test: if one key assumption is wrong, how much of the work cascades? High cascade = fragile coordination. Low cascade = robust coordination
Coherence Test:
┌────────────────────────────────────┬─────────────────────────────────┐
│ Check                              │ Result                          │
├────────────────────────────────────┼─────────────────────────────────┤
│ Sub-task outputs compatible?       │ Yes / No / Partially            │
│ Tool calls non-redundant?          │ Yes / No (list repeats)         │
│ Direction aligned with request?    │ Yes / Drifted (describe)        │
│ Single-assumption cascade risk?    │ Low / Medium / High             │
└────────────────────────────────────┴─────────────────────────────────┘

Expected: A concrete assessment of overall coherence with specific issues identified. Coherent coordination should feel like parts clicking together; incoherent coordination feels like forcing puzzle pieces.

On failure: If coherence is poor, identify the specific point where sub-tasks diverge. Often it is a single stale assumption or an unprocessed user correction that propagated through downstream work. Fix the point of divergence, then re-verify downstream outputs.

Validation

  • Coordination problem was classified by type
  • Information decay rates were considered for facts relied upon
  • Local protocols were applied (especially Safety and Deposit)
  • Freshness audit identified stale information (or confirmed freshness with evidence)
  • Emergent coherence was tested across sub-tasks
  • Inhibition signals were respected (tried-and-failed approaches not repeated)

Common Pitfalls

  • Over-engineering signals: Complex coordination protocols slow work more than they help. Start with Safety + Deposit; add others only when problems emerge
  • Trusting stale context: The most common coordination failure is relying on information that was true 20 messages ago but has since been updated or invalidated. When in doubt, re-read
  • Ignoring inhibition signals: Retrying a failed approach without changing anything is not persistence — it is ignoring the failure signal. Something must be different for a retry to succeed
  • No deposits: Completing sub-tasks without noting their outputs forces later sub-tasks to re-derive or re-read. Brief summaries save significant re-work
  • Assuming coherence: Not testing whether sub-tasks actually combine into a coherent whole. Each sub-task can be correct independently but incoherent collectively — the integration is where coordination fails

Related Skills

  • coordinate-swarm — the multi-agent coordination model that this skill adapts to single-agent reasoning
  • forage-solutions — coordinates exploration across multiple hypotheses
  • build-coherence — coordinates evaluation across competing approaches
  • heal — deeper assessment when coordination failures reveal subsystem drift
  • awareness — monitors for coordination breakdown signals during execution

平台分布

Codex

36.23%
按下载量换算54

Claude

33.6%
按下载量换算50

Cursor

17.68%
按下载量换算26

Gemini CLI

9.39%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills