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Agent Skill · 开发

grc-planner(GRC 规划师)

grc-planner 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

grc-planner 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 19,470。

总安装 269周安装 11GitHub Stars 公开资料未说明下载 87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:grc-planner(GRC 规划师)
来源仓库:https://github.com/pinkie1301/grc-skills
仓库路径:skills/grc-planner
安装命令:
npx skills add https://github.com/pinkie1301/grc-skills --skill grc-planner
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/pinkie1301/grc-skills --skill grc-planner

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。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在需要围绕仓库状态或代码变更进行整理时使用。可结合来源仓库 README 核验具体用法,支持主流宿主环境。安装前建议确认权限范围和是否会触发联网或文件读写。

安装方式:通过 GitHub 仓库安装,适用于 Codex、Claude 等工具。

来源仓库内路径:skills/grc-planner

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/pinkie1301/grc-skills --skill grc-planner;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

grc-planner 怎么安装?

在终端执行 npx skills add https://github.com/pinkie1301/grc-skills --skill grc-planner。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

grc-planner 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。

grc-planner 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

grc-planner 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。

grc-planner 用的人多吗?

公开数据是累计安装 269 次,近一周安装 11 次,下载 87 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。

grc-planner 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

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。

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
grc-planner

GRC 规划师 · 本页

269—只读未明确通过

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

GRC Planner

Purpose

Convert GNU Radio .grc change requests into a structured, execution-ready implementation plan.

Scope

  • Accept a .grc file and requested architecture changes.
  • First run an interactive readiness check.
  • Produce one Markdown plan file only after all planning blockers are resolved, or after the user explicitly asks for a draft with TODOs.
  • Split work into explicit phases.
  • Cover block changes, parameter changes, and connection rewiring.
  • Include dedicated handling for Python code changes in Python Block or Embedded Python Block.
  • Require parameter verification for every added or modified block.

Output Requirements

  • Determine READY_TO_WRITE before creating or writing any plan file.
  • Generate exactly one plan file named plan_{title_name}.md only when READY_TO_WRITE is true.
  • Write the plan body in Traditional Chinese.
  • Keep all implementation details actionable and ordered by phase.
  • Include touched blocks, parameter updates, and connection rewiring details.
  • If READY_TO_WRITE is false, respond only with a concise blocker summary and at most 3 clarification questions. Do not include a partial plan, template body, phase table, or Markdown plan file.
  • Do not write the final plan file until interaction blockers are resolved, unless the user explicitly asks for a draft with TODOs.

Template Policy

  • Use plan template as the primary output structure.
  • The template is written in Traditional Chinese.
  • Do not translate or rewrite the template unless the user explicitly requests template edits.

Filename Rules

  1. Prefix with plan_.
  2. Use a readable title_name.
  3. Optionally append a version suffix such as _v1, _v2, _v3.
  4. Replace whitespace with _.
  5. Remove forbidden filename characters: \\ /: *? " < > |.

Example:

  • Title: QPSK FEC 1/2 TX Chain Migration
  • Output: plan_QPSK_FEC_1_2_TX_Chain_Migration_v1.md

Required Inputs

  • Current .grc file (or equivalent flowgraph artifact).
  • Target behavior and change constraints.
  • Any phase preference (for example TX-first, RX-first, or cutover sequence).
  • Risk boundaries and known deployment constraints.

Interactive Planning Policy

  • Treat the readiness gate as a hard stop, not a suggestion.
  • Use an interactive planning loop when missing or ambiguous information could change topology, block selection, verified parameters, connection rewiring, Python block behavior, phase ordering, or deployment risk.
  • Ask concise clarification questions before writing plan_{title_name}.md when required inputs are missing.
  • Ask at most 3 questions at a time.
  • After asking clarification questions, stop the current response. Do not continue into plan generation in the same response.
  • Prefer concrete implementation questions over broad discussion.
  • State safe assumptions and continue when the assumption does not change architecture, runtime behavior, or risk boundaries.
  • If the user asks for a draft despite unresolved questions, continue with explicit TODO markers for each unresolved decision.
  • Do not use unresolved assumptions as verified block parameters or connection facts.
  • After each user answer, update the working plan state and continue from the first still-blocked workflow step.

Workflow

Step 0: Interactive clarification gate

  1. Before writing any file or plan body, decide whether the plan is READY_TO_WRITE.
  2. Set READY_TO_WRITE=true only when all of these are satisfied:

- Current .grc file or equivalent flowgraph artifact is available. - Target behavior is concrete enough to determine topology. - Touched blocks can be identified. - Ambiguous block choices are resolved. - Phase ordering risk is resolved, explicitly specified, or safely irrelevant. - Required block parameters can be verified, or unresolved parameters are allowed because the user explicitly requested a draft with TODOs.

  1. Set READY_TO_WRITE=false when any missing or ambiguous detail could change architecture, runtime behavior, verified parameters, connection facts, phase ordering, or deployment risk.
  2. If READY_TO_WRITE=false, stop and ask only the questions needed to unblock the next planning step.
  3. Ask at most 3 questions and do not generate a plan body, template body, or output file in that response.
  4. Continue without asking only when missing details can be safely represented as explicit TODOs and the user has requested a draft.
  5. Repeat this gate after baseline mapping and parameter verification if new blockers appear.

Step 1: Collect context

  1. Read the target .grc and the user request.
  2. Identify whether Python code is embedded in .grc or external.
  3. Record all touched artifacts that must be reflected in the plan.

Step 2: Build baseline map

  1. Extract current blocks (name, id) and current connections.
  2. Identify current TX/RX/header/payload/tag boundaries when relevant.
  3. Mark the gaps between current and desired topology.
  4. If the target topology cannot be determined from the request, ask follow-up questions before designing phases.

Step 3: Verify block parameters (mandatory)

For every added or modified block:

  1. Retrieve GRC parameter definitions via grc-block-query.
  2. Never infer fields from memory.
  3. Prefer canonical GRC GUI parameter definitions from block YAML.
  4. If lookup returns not_found, keep unresolved fields as explicit TODO items.
  5. If multiple plausible GRC blocks match the requested behavior, ask the user to choose before planning rewiring.

When using grc-block-query, verify these JSON fields:

  • status
  • source
  • source_location
  • entry.fields (or __grc_parameters__ for full parameter set)
  • db_file (when cache update is enabled)

Query examples:

  • From repo root: python./skills/grc-block-query/scripts/query_grc_blocks.py --block "<block name>"
  • From grc-block-query root: python./scripts/query_grc_blocks.py --block "<block name>"
  • Field-specific lookup: --field "<field name>"

Shared DB notes:

  • Shared DB root is ~/Documents/grc-block-query/db.
  • Prefer local DB evidence first.
  • If source is external, ensure traceability fields are present.

Step 4: Design phased implementation

  1. Convert the migration path into phases with clear ordering.
  2. For each phase, include:
  • phase objective
  • touched blocks
  • parameter updates (with verified sources)
  • connection rewiring
  • acceptance criteria
  1. If phase order affects risk or deployment continuity and no preference is provided, ask before finalizing the plan.

Step 5: Handle Python block changes explicitly

If Python Block or Embedded Python Block is touched, include:

  1. Block identity (name and id).
  2. Current code location (.grc embedded section or external file).
  3. A line-level separated comparison with 修改前 and 修改後 sections. Do not use diff fenced blocks, + prefixes, or - prefixes for code changes.
  4. Full post-change code in a python fenced block.
  5. Notes for imports/classes/functions that affect other blocks.
  6. Explicit TODO markers for unresolved unknowns.

Step 6: Assemble final plan

  1. Re-run Step 0 and confirm READY_TO_WRITE=true.
  2. If READY_TO_WRITE=false, return to Step 0 and stop after asking clarification questions.
  3. Write plan_{title_name}.md.
  4. Keep each phase directly executable.
  5. Ensure every touched block has parameter and connection evidence.
  6. Ensure unresolved items are explicit TODOs (no guessed values).

Quality Checklist

  • Every touched block is listed.
  • Every added or modified block includes verified parameter definitions.
  • Every parameter source is traceable.
  • Every connection change is explicit.
  • Python block changes include separated before/after code comparison and full updated code when applicable.
  • Interaction blockers were resolved, or unresolved decisions are marked as TODOs because the user requested a draft.
  • No fabricated values are introduced.
  • The output filename follows naming rules.

Prohibitions

  • Do not invent block fields or defaults.
  • Do not silently omit unresolved parameters.
  • Do not treat runtime CLI arguments as GRC GUI parameter definitions.
  • Do not rewrite the template file during planning output generation.

平台分布

Codex

37.45%
按下载量换算33

Claude

30.8%
按下载量换算27

Cursor

19.77%
按下载量换算17

Gemini CLI

9.45%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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