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Agent Skill · 开发

meaningful-chunker(有意义的分块器)

meaningful-chunker 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

meaningful-chunker 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 6,789。

总安装 4,343周安装 174GitHub Stars 1下载 1,406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
1.2.2

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:meaningful-chunker(有意义的分块器)
来源仓库:https://github.com/daymyandogg/meaningful-chunker
安装命令:
openclaw skills install meaningful-chunker
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 meaningful-chunker

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

基于图形化架构分析代码库,提供智能查询与安全评估能力。适用于大型项目理解、重构决策与系统漏洞排查场景。支持跨文件关系可视化与依赖追踪,提升开发效率。meaningful-chunker 属于开发类 Skill,可作为该场景下的辅助能力补充。使用前需索引目标代码仓库,确保权限覆盖所有相关文件。

注意:深度分析可能消耗较多计算资源,建议在非高峰时段运行。

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 meaningful-chunker;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

    它需要接触敏感数据,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

meaningful-chunker 怎么安装?

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

meaningful-chunker 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。

meaningful-chunker 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

meaningful-chunker 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。

meaningful-chunker 用的人多吗?

公开数据是累计安装 4,343 次,近一周安装 174 次,下载 1,406 次,GitHub 1 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。

meaningful-chunker 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

  • 需要接触敏感数据,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。
  • 需要处理开发类任务、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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
meaningful-chunker

有意义的分块器 · 本页

4,3431接触敏感数据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
meaningful-chunker
description
Graph-based code intelligence API. Query any indexed codebase for architecture understanding, debugging, refactor safety analysis, and design principle mapping. Returns structured analysis with ranked chunks, execution paths, root-cause chains, and answer synthesis. Use when asked to analyze codebases, explain what a component does, trace a bug to its source, assess whether a change is safe, or understand the design principles governing a system.
version
1.2.2
metadata
openclaw
emoji
🧠
homepage
https://github.com/DaymyanDogg/Meaningful-Chunker
requires
env
primaryEnv
CHUNKER_API_KEY

Meaningful Chunker — Code Intelligence API

A graph-based code analysis system that scans any codebase once, builds a semantic graph of all components and their relationships, then answers natural-language queries against that graph. Returns structured, ranked results with explanation — not raw file dumps.


⚠️ Required First Step

You MUST scan a codebase before using any query endpoints.

If you skip this, all queries will fail with a no_scan_loaded error.

Always start with POST /scan. See the Scanning a Codebase section below.


🔐 Authentication Required

All endpoints except /health and /status require an API key.

Include this header in every request:

x-api-key: YOUR_API_KEY

Without this header, requests return 401 Unauthorized. Set your key as CHUNKER_API_KEY in your agent's environment.


Setup

Two environment variables are required before using this skill:

CHUNKER_API_URL   — Base URL of the hosted API.
                    Example: https://meaningful-chunker-production.up.railway.app
CHUNKER_API_KEY   — Your API key. Get a free key instantly at:
                    https://meaningful-chunker-production.up.railway.app/register/free
                    (100 queries/month, resets each calendar month, no credit card required)
                    Upgrade to Pro (2,000/month) at /upgrade.

Full OpenAPI spec available at: $CHUNKER_API_URL/docs


When to Use This Skill

Use one of the four query endpoints depending on intent:

IntentEndpointExample query
Understand what something does/query/architecture"What does the authentication module do?"
Trace a bug or failure/query/debug"Why is the login function failing?"
Assess safety of a change/query/refactor"Can I safely change the database connector?"
Understand design principles/query/philosophy"What principle governs error handling here?"

All four endpoints accept the same request body and return the same response shape.


🚀 30-Second Quick Start

  1. Scan a repo:

POST /scan with {"repo_url": "https://github.com/owner/repo"}

  1. Wait until:

GET /status → "ready": true

  1. Query:

POST /query/architecture with {"query": "What does X do?"}

Scanning a Codebase


Scan a GitHub repo (recommended)

curl -s -X POST $CHUNKER_API_URL/scan \
  -H "Content-Type: application/json" \
  -H "x-api-key: $CHUNKER_API_KEY" \
  -d '{"repo_url": "https://github.com/owner/repo"}'

The system clones the repo, builds the graph, and deletes the local clone automatically. Supports any public GitHub, GitLab, or git URL — including /tree/main branch URLs. Repos larger than 300MB are rejected with a clear error.

Scan a local path (self-hosted instances only)

curl -s -X POST $CHUNKER_API_URL/scan \
  -H "Content-Type: application/json" \
  -H "x-api-key: $CHUNKER_API_KEY" \
  -d '{"project_path": "/path/to/project"}'

Check scan progress

curl $CHUNKER_API_URL/status

When "ready": true the graph is built and all query endpoints are available. Scanning typically takes 5–30 seconds depending on repo size.


How to Query

Request format

curl -s -X POST $CHUNKER_API_URL/query/architecture \
  -H "Content-Type: application/json" \
  -H "x-api-key: $CHUNKER_API_KEY" \
  -d '{"query": "What does the payment processor do?"}'

Replace /query/architecture with the appropriate endpoint for your intent.

Optional: session continuity

Pass a session_id to maintain context across related queries. The system remembers what you asked recently and biases results toward the same area of the codebase.

curl -s -X POST $CHUNKER_API_URL/query/debug \
  -H "Content-Type: application/json" \
  -H "x-api-key: $CHUNKER_API_KEY" \
  -d '{"query": "Why is the checkout flow failing?", "session_id": "my-investigation-001"}'

⚡ Quick Read Guide

For fastest results, read the response in this order:

  1. answer_summary — one sentence telling you what the key component is and why it matters. Start here every time.
  2. primary_path — the execution chain (A → B → C). Shows how things connect structurally.
  3. CENTER tier chunks — the exact matches. These ARE the answer.
  4. EPIPHANY tier chunks — critical cross-system connections. Don't skip these.
  5. next_step — actionable follow-up already computed for you.

Everything else (BREAKTHROUGH, RELEVANT) is supporting context. Read it when you need depth, skip it when you don't.


Understanding the Response

Top-level synthesis fields

answer_summary      — One-sentence synthesis. Start here. Tells you what the
                      key component is, its role, and why it matters.

system_explanation  — What the relevant subsystem does as a whole. Multiple
                      components explained together.

primary_path        — The execution chain: "A → B → C". Shows how components
                      connect structurally. Most useful for debugging.

query_profile       — Which intent was detected (architecture/debug/refactor_risk/
                      philosophy). Confirms the system understood your query.

confidence          — "high" / "medium" / "low". Trust signal before reading context.

next_step           — Actionable follow-up. What to look at next.

Debug-specific fields (present on /query/debug responses)

root_cause_analysis.execution_timeline    — Call chain with [FAILING_CHUNK] bracketed
root_cause_analysis.root_cause_hypotheses — Ranked suspects with confidence + check instructions
root_cause_analysis.top_suspect           — Single highest-suspicion chunk with specific check

Refactor-specific fields (present on /query/refactor responses)

structural_authority.change_risk   — "untouchable" / "sensitive" / "local"
structural_authority.blast_radius  — How many chunks/files break if this changes
top_risks                          — Top 5 most dangerous chunks in the whole codebase

Context tiers

CENTER       (score=100)  — Exact match. This IS what you asked about.
EPIPHANY     (score≥99)   — Critical cross-component connection. Don't skip these.
BREAKTHROUGH (score≥82)   — Direct structural dependency. Important context.
RELEVANT     (score≥70)   — Meaningful but peripheral. Useful for broader understanding.

Each chunk includes:

  • name — component identifier
  • type — class / function / method / module_code / etc.
  • file — source file path
  • summary — one-line description
  • why_matched — how the system found this chunk
  • neighbors — adjacent components in the graph
  • explanation (CENTER/EPIPHANY only) — roles, primary reason, importance summary

Example: Architecture Query

curl -s -X POST $CHUNKER_API_URL/query/architecture \
  -H "Content-Type: application/json" \
  -H "x-api-key: $CHUNKER_API_KEY" \
  -d '{"query": "What does the UserAuthenticator do?"}'

Read: answer_summary → primary_path → CENTER explanation.roles → BREAKTHROUGH neighbors


Example: Debug Query

curl -s -X POST $CHUNKER_API_URL/query/debug \
  -H "Content-Type: application/json" \
  -H "x-api-key: $CHUNKER_API_KEY" \
  -d '{"query": "Why is the login flow not working?"}'

Read: root_cause_analysis.top_suspect → execution_timeline → root_cause_hypotheses[0]


Example: Refactor Safety Query

curl -s -X POST $CHUNKER_API_URL/query/refactor \
  -H "Content-Type: application/json" \
  -H "x-api-key: $CHUNKER_API_KEY" \
  -d '{"query": "Can I safely change the database connection handler?"}'

Read: structural_authority.change_risk → blast_radius → advice → top_risks


Relevance Tiers — Scoring Reference

TierScoreWhat it means
CENTER100Exact match — this IS the answer
EPIPHANY≥99Critical cross-system connection
BREAKTHROUGH≥82Direct structural dependency
RELEVANT≥70Meaningful peripheral context

Results capped at: CENTER×3, EPIPHANY×5, BREAKTHROUGH×6, RELEVANT×5. Max 19 chunks per response.


Checking API Health

These endpoints are always open — no API key required:

curl $CHUNKER_API_URL/health

Returns {"status": "ok"} when the system is up and a project is indexed.

curl $CHUNKER_API_URL/status

Returns current graph stats: chunk count, edge count, cluster count, shortcut count, last scan time.


⚠️ Common Issues

  • "no_scan_loaded" → You forgot to run /scan
  • 401 Unauthorized → Missing x-api-key header

Notes

  • Queries are natural language — no special syntax required. "Why is X broken?" works as well as "explain the architecture of X."
  • The system is language-agnostic: Python, C++, JSON, Markdown, and plain text files are all indexed.
  • Session memory persists within an API session (same session_id). Cross-session long-term focus is tracked via insight memory — frequently queried components surface higher automatically.
  • Repo scans maintain memory during the active service lifecycle. The same repo URL will accumulate focus signals across queries until the service restarts.
  • Large repos (10k+ files) may take up to 2 minutes to scan. Poll /status to check progress.

平台分布

OpenClaw

81.18%
按下载量换算1,141

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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