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Agent Skill · 研究检索

coding-lead(编码引线)

coding-lead 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

coding-lead 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,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 2,542。

总安装 59,081周安装 2,390GitHub Stars 公开资料未说明下载 18,546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-0
版本
3.0.6

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:coding-lead(编码引线)
来源仓库:https://github.com/beyound87/coding-lead
安装命令:
openclaw skills install coding-lead
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install coding-lead

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。

Coding-lead 为实施型代理提供编码执行支持,当前仅支持 Claude 生产路径。适合简单任务直连与中等任务 ACP 运行模式切换。通过分级策略优化资源分配,平衡速度与准确性。在 OpenClaw 中通过 clawhub 安装,需配置 Claude 服务密钥。使用前应评估任务复杂度,避免误用导致延迟或成本上升。

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 OpenClaw;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 openclaw skills install coding-lead;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

coding-lead 怎么安装?

在终端执行 openclaw skills install coding-lead。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

coding-lead 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

coding-lead 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 openclaw skills install coding-lead 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。

coding-lead 是免费的吗?

来源标注的许可证是 MIT-0。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。

coding-lead 用的人多吗?

公开数据是累计安装 59,081 次,近一周安装 2,390 次,下载 18,546 次。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。

coding-lead 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,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 OpenClaw,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
coding-lead

编码引线 · 本页

59,081—执行命令MIT-0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

name
coding-lead
description
Coding execution skill for any implementation-focused agent. Current production path is claude-only with simple tasks direct, medium tasks preferring ACP run or direct acpx, and complex tasks handled via existing agent continuity plus context files instead of ACP session persistence. Integrates with qmd and smart-agent-memory when available.

Coding Lead

This is a coding execution skill for any agent that owns implementation work. It defines how coding work runs, not who should own the task. In multi-agent teams, routing may be handled elsewhere; in single-agent use, this skill still works directly.

Route by complexity. Current production path is claude-only. Do not depend on ACP session persistence in IM threads; use direct execution, direct acpx, and existing implementation session continuity instead.

Task Classification

LevelCriteriaAction
SimpleSingle file, <60 lines, clear local scopeDirect: read/write/edit/exec
Medium2-5 files, clear scope, likely follow-up questionsPrefer Claude ACP mode:"run" or direct acpx → fallback direct
ComplexMulti-module, architecture, needs continuityUse existing implementation session continuity + context files + direct acpx/direct execution

When in doubt, go one level up.

Practical default rule

  • Simple: stay in the current session; do not open ACP unless clearly beneficial
  • Medium: prefer Claude ACP one-shot (run) when available; otherwise direct acpx
  • Complex: preserve continuity through the existing implementation session, on-disk context files, and serial follow-ups; do not make IM-bound ACP session the default path
  • ACP unavailable: medium/complex fall back to direct acpx or direct execution; simple tasks were already direct by default
  • Never block on ACP availability: ACP is an accelerator, not a hard dependency

Multi-agent dispatch rule (when dispatching to other agents)

  • Dispatch to ACP-configured agents (agents with runtime.type: "acp" in openclaw.json): use sessions_spawn(runtime="acp"), may include streamTo="parent"
  • Dispatch to standard agents (all others): use sessions_spawn(runtime="subagent"), never include streamTo
  • Results from subagent spawns arrive via auto-announce, not polling
  • How to tell which is which: check the target agent's config in openclaw.json — if it has runtime.type: "acp", use ACP; otherwise use subagent

Tech Stack (New Projects)

LayerPreferredFallback
BackendPHP (Laravel/ThinkPHP)Python
FrontendVue.jsReact
MobileFlutterUniApp-X
CSSTailwind-
DBMySQLPostgreSQL

Existing projects: follow current stack. New: propose first, wait for confirmation.

Tool Detection & Fallback

All tools are optional. Detect once per session:

ToolCheckFallback
smart-agent-memorynode ~/.openclaw/skills/smart-agent-memory/scripts/memory-cli.js stats ok?memory_search + manual .md writes
qmdqmd --version ok?grep (Linux/macOS) / Select-String (Windows) / find
ACPSee ACP detection belowDirect read/write/edit/exec

Notation: [memory] [qmd] [acp] = use if available, fallback if not.

ACP Detection & Routing

Run once per session, stop at first success:

Step 1: Try sessions_spawn (timeout: 30s)

sessions_spawn(runtime: "acp", agentId: "claude", task: "say hello", mode: "run", runTimeoutSeconds: 30)

Preferred in OpenClaw because it cleanly supports both:

  • mode: "run" for one-shot coding tasks
  • mode: "session" for persistent long-context coding threads
  • Got a reply → ACP_MODE = "spawn". Done.
  • Error or no reply within 30s → kill session, go to Step 2.

Step 2: Try acpx CLI (timeout: 30s)

# Detect acpx path (OS-dependent)
# Windows: %APPDATA%\
pm\
ode_modules\openclaw\extensions\acpx\
ode_modules\.bin\acpx.cmd
# macOS/Linux: $(npm root -g)/openclaw/extensions/acpx/node_modules/.bin/acpx

# Use exec with timeout
acpx claude exec "say hello"   # timeout 30s
  • Got a reply → ACP_MODE = "acpx". Done.
  • Error, empty output, or stuck beyond 30s → kill process, go to Step 3.

Step 3: No ACP available

ACP_MODE = "direct". Agent executes all coding tasks directly with read/write/edit/exec. Load team standards (see Coding Standards below).

Cache the result

Set a session variable (mental note): ACP_MODE = "spawn" | "acpx" | "direct"

  • Cache lifetime = current session. Each new session re-detects once. Keep the detection note minimal and refresh it whenever the underlying mode stops working.
  • If a cached mode fails mid-session (e.g. acpx suddenly errors), re-run detection from Step 1.

ACP Agent Policy

Current supported ACP coding agent: claude only.

  • Do not route coding work to codex or other future agents in the production path yet.
  • If a request merely mentions ACP or coding-agent execution without naming a different approved agent, default detection and execution guidance to Claude.
  • If documentation mentions other coding agents, treat them as future possibilities only, not current operating policy.
  • Code review can still be done by the coordinating OpenClaw agent, but ACP execution guidance in this skill is claude-only.

Rule Priority

Apply rules in this order:

  1. Matched skill instructions (this skill wins for coding execution when loaded)
  2. Agent role fallback only when the coding skill is not loaded or does not cover the case
  3. Team templates / README / generated docs provide boundaries and ownership, not competing execution logic

If the same topic appears in multiple places, follow the highest-priority source above and simplify the lower-priority wording instead of combining conflicting chains.

Context File Lifecycle

Context files exist to preserve continuity across the current code chain, but they must stay tidy.

  • Store active context files under <project>/.openclaw/
  • Use a stable name per task chain: context-<task-slug>.md
  • Reuse the same file for the same chain; do not create a new file every turn
  • Active context file cap per project: 60
  • Context-file lifecycle window per project: 100 total files (active + archive). When approaching the limit, prune stale archived files first, then merge or remove low-value active chains only if truly superseded.
  • When a task is completed, either delete the temporary context file or move it under .openclaw/archive/ if it has durable follow-up value
  • If a file is stale, ownerless, or superseded by a newer chain, treat it as cleanup/archive candidate
  • Before creating a new active context file, check whether an existing file for that chain can be reused

Context Naming

Recommended pattern:

  • <project>/.openclaw/context-<task-slug>.md
  • task slug should be short, stable, and human-readable
  • avoid timestamp-only names for active files unless the task truly has no durable identifier

Coding Standards — Two Layers, No Overlap

Layer 1: Project-level (Claude Code owns)

Projects may have their own CLAUDE.md, .cursorrules, docs/ — these are Claude Code's responsibility. It reads them automatically. Do NOT paste project-level rules into ACP prompts.

Layer 2: Team-level (OpenClaw owns)

shared/knowledge/tech-standards.md — cross-project standards (security, change control, tech stack preferences). Only relevant for direct execution (simple tasks without ACP).

When spawning ACP

  • Don't embed coding standards in the prompt — Claude Code has its own CLAUDE.md
  • Do include: task description, acceptance criteria, relevant context (file paths, decisions)
  • Do include task-specific constraints if any (e.g., "don't change the API contract")

When executing directly (no ACP)

Load standards once per session, first match wins:

  1. shared/knowledge/tech-standards.md (team-level, if exists)
  2. Built-in defaults (below, if nothing exists)

Built-in Defaults (fallback for direct execution)

  • KISS + SOLID + DRY, research before modifying
  • Methods <200 lines, follow existing architecture
  • No hardcoded secrets, minimal change scope, clear commits
  • DB changes via SQL scripts, new tech requires confirmation

Simple Tasks

  1. Read target file(s) (standards already loaded per above)
  2. [memory] Recall related decisions
  3. Execute with read/write/edit/exec
  4. [memory] Record what changed and why

Medium/Complex Tasks

Step 1: Build Context File

Write to <project>/.openclaw/context-<task-id>.md (ACP reads from disk, not from prompt):

# [qmd] or grep: find relevant code
# [memory] recall + lessons: find past decisions
# Standards already loaded (see "Coding Standards Loading" above)
# Write context file with 3-5 key rules from loaded standards — do NOT paste full file

Minimal context file structure:

# Task Context: <id>
## Project — path, stack, architecture style
## Relevant Code — file paths + brief descriptions from qmd/grep
## History — past decisions/lessons from memory (if any)
## Long-term Knowledge Boundary — durable facts or decisions worth preserving outside this file; if none, say "none"
## Constraints — task-specific rules only (NOT general coding standards — Claude Code has CLAUDE.md)

Full template with examples → see references/prompt-templates.md

Step 2: Lean Prompt

Use the smallest prompt that still preserves correctness. Start with the task and acceptance criteria. Add only the minimum extra header needed for the run to be unambiguous.

Project: <path> | Stack: <e.g. Laravel 10 + React 18 + TS>
Context file: .openclaw/context-<task-id>.md (read it first if it exists)

## Task
<description>

## Acceptance Criteria
- [ ] <criteria>
- [ ] Tests pass, no unrelated changes, clean code

Before finishing: run linter + tests, include results.
When done: openclaw system event --text "Done: <summary>" --mode now

Step 3: Spawn (use detected ACP_MODE)

# ACP_MODE = "spawn", medium task:
sessions_spawn(runtime: "acp", agentId: "claude", task: <prompt>, cwd: <project-dir>, mode: "run")

# Complex task primary path:
Use the existing implementation session + context file + serial follow-ups.
If ACP is helpful, prefer bounded Claude `run` invocations or direct acpx commands inside the project directory.

# ACP_MODE = "acpx":
exec: cd <project-dir> && acpx claude exec "<prompt>"

# ACP_MODE = "direct":
Skip spawn, execute directly with read/write/edit/exec

run vs sustained execution

  • run: one-shot, bounded Claude ACP coding task
  • sustained execution: for repeated follow-up on the same code chain, keep working in the existing implementation conversation/session and persist context on disk; do not rely on IM-bound ACP thread/session support
  • direct fallback: when ACP is unavailable or unstable, execute directly with read/write/edit/exec instead of stalling

Step 4: Fallback Detection

ConditionAction
Spawn failed / timeout→ Direct execution
Empty output / no file changes→ Direct execution
Partial completion→ Agent fixes remaining

Fallback: [memory] log failure → agent executes directly → report to user.

Never silently fail. Always complete or report why not.

Step 5: Verify & Record

  1. Check acceptance criteria + run tests
  2. Verify the final result against the task, acceptance criteria, and any explicit no-go constraints before declaring done
  3. [memory] Record: what changed, decisions, lessons; only promote durable facts to long-term memory
  4. Clean up context file

Complex Tasks

Read references/complex-tasks.md only for Complex-level tasks — roles, QA isolation, parallel strategies, RESEARCH→PLAN→EXECUTE→REVIEW flow.

Context Reuse (Token Savings)

  • Context file on disk instead of prompt embedding → major token savings per spawn
  • Simple tasks stay direct: don't pay ACP/session overhead for tiny edits
  • Medium tasks use run: cheaper than opening a persistent session
  • Complex tasks use sustained session continuity: preserve continuity through the existing implementation session plus context files
  • Serial follow-ups: continue in the same implementation conversation and refresh the on-disk context file as the task evolves
  • [qmd]: precision search → only relevant snippets in context file
  • No standards in ACP prompts: Claude Code reads its own CLAUDE.md/.cursorrules — don't duplicate
  • ACP prompt stays lean: task + acceptance criteria + context file path. No generic rules
  • Direct execution: load team standards once per session, not per task

Memory Integration

[memory] Before: recall related work + lessons for context file. [memory] After: record what changed, decisions made, lessons learned. Cross-session: agent remembers across sessions; Claude Code doesn't. This is the core advantage.

Parallel Execution Boundaries

Parallelism is allowed in the current production path, but only with explicit boundaries.

  • Hard cap: 5 concurrent work units total
  • Active context files per project must stay <= 60
  • Total context files per project should stay <= 100 across active + archive
  • Define boundaries first: by project, by module, by task stage, or by owner
  • Never let two work units modify the same code chain, same file cluster, or same acceptance scope
  • Parallel work must have a merge owner and an acceptance owner before execution starts
  • If boundaries are fuzzy, collapse back to sequential execution

Recommended shape:

  • 1 coordinating implementation session
  • up to 4 additional bounded work units (Claude ACP run, direct acpx, or direct execution)

Good parallel cases:

  • independent products
  • different modules with separate files and acceptance criteria
  • one bounded Claude ACP run while direct tasks proceed elsewhere

Bad parallel cases:

  • same bug chain
  • same module with shared intermediate state
  • duplicate research on the same problem
  • implementation and delivery work both editing the same area

See references/prompt-templates.md for multi-project examples.

Smart Retry (max 3)

  1. Analyze failure → 2. Adjust prompt → 3. Retry improved → 4. Max 3 then fallback/report.

Each retry must be meaningfully different.

Progress Updates

Start → 1 short message. Error → immediate report. Completion → summary. Fallback → explain.

Safety

  • Never spawn in ~/.openclaw/ — coding agents may damage config
  • Always inspect and confirm the intended working directory before spawning or writing; then set cwd explicitly to the project directory
  • Review before commit — especially complex tasks
  • Kill runaway sessions — timeout or nonsensical output

See Also

平台分布

OpenClaw

73.21%
按下载量换算13,578

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install coding-lead 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。目前只有一个公开来源,建议同时核对源仓库。

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