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Agent Skill · 研究检索

protocol-authoring(协议编写)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

protocol-authoring 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 66,285。

总安装 267周安装 11GitHub Stars 24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:protocol-authoring(协议编写)
来源仓库:https://github.com/noobygains/godmode
仓库路径:skills/protocol-authoring
安装命令:
npx skills add https://github.com/noobygains/godmode --skill protocol-authoring
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/noobygains/godmode --skill protocol-authoring

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。

protocol-authoring 用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时需先确认最小权限、脱敏方式和操作边界。

通过 npx skills add 命令从指定 GitHub 仓库安装并使用。建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/protocol-authoring

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/noobygains/godmode --skill protocol-authoring;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

protocol-authoring 怎么安装?

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

protocol-authoring 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。

protocol-authoring 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。

protocol-authoring 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。

protocol-authoring 用的人多吗?

公开数据是累计安装 267 次,近一周安装 11 次,下载 87 次,GitHub 24 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。

protocol-authoring 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
protocol-authoring

协议编写 · 本页

26724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

Protocol Authoring

Overview

Authoring protocols IS Test-Driven Development applied to process documentation.

Personal protocols live in agent-specific directories (~/.claude/skills for Claude Code, ~/.agents/skills/ for Codex)

You design test scenarios (pressure-based exercises with subagents), observe failure (baseline behavior), author the protocol (documentation), observe compliance (agents follow the protocol), and harden (seal loopholes).

Core principle: If you never observed an agent fail without the protocol, you cannot know what the protocol needs to prevent.

REQUIRED BACKGROUND: You MUST understand godmode:test-first before using this skill. That skill defines the foundational RED-GREEN-REFACTOR cycle. This skill adapts TDD to documentation.

What is a Protocol?

A protocol is a reference guide for proven techniques, patterns, or tools. Protocols help future Claude instances discover and apply effective approaches.

Protocols are: Reusable techniques, patterns, tools, reference guides

Protocols are NOT: Narratives about how you solved something once

TDD Mapping for Protocols

TDD ConceptProtocol Creation
Test casePressure scenario with subagent
Production codeProtocol document (SKILL.md)
Test fails (RED)Agent breaks rule without protocol (baseline)
Test passes (GREEN)Agent complies when protocol is present
RefactorSeal loopholes while maintaining compliance
Write test firstRun baseline scenario BEFORE authoring protocol
Watch it failRecord exact rationalizations the agent uses
Minimal codeAuthor protocol addressing those specific violations
Watch it passConfirm agent now complies
Refactor cycleDiscover new rationalizations, plug them, re-verify

The entire protocol creation process follows RED-GREEN-REFACTOR.

When to Create a Protocol

Create when:

  • The technique was not intuitively obvious to you
  • You would reference this again across multiple projects
  • The pattern applies broadly (not project-specific)
  • Others would benefit from it

Do not create for:

  • One-off solutions
  • Standard practices well-documented elsewhere
  • Project-specific conventions (put those in CLAUDE.md)
  • Mechanical constraints (if enforceable with regex or validation, automate it — save documentation for judgment calls)

Protocol Categories

Technique

Concrete method with steps to follow (event-based-waiting, root-cause-tracing)

Pattern

Cognitive framework for approaching problems (flatten-with-flags, test-invariants)

Reference

API documentation, syntax guides, tool documentation (office docs)

Directory Layout

skills/
  protocol-name/
    SKILL.md              # Primary reference (required)
    supporting-file.*     # Only when necessary

Flat namespace — all protocols in one searchable namespace

Separate files for:

  1. Dense reference material (100+ lines) — API docs, comprehensive syntax
  2. Reusable tools — Scripts, utilities, templates

Keep inline:

  • Principles and concepts
  • Code patterns (under 50 lines)
  • Everything else

SKILL.md Structure

Frontmatter (YAML):

  • Only two fields supported: name and description
  • Max 1024 characters total
  • name: Letters, numbers, and hyphens only (no parentheses or special characters)
  • description: Third-person, describes ONLY when to use (NOT what it does)

- Start with "Use when..." to focus on trigger conditions - Include specific symptoms, situations, and contexts - NEVER summarize the protocol's process or workflow (see Discovery Optimization section) - Keep under 500 characters if possible

---
name: Protocol-Name-With-Hyphens
description: Use when [specific trigger conditions and symptoms]
---

# Protocol Name

## Overview
What is this? Core principle in 1-2 sentences.

## When to Use
[Small inline flowchart IF decision non-obvious]

Bullet list with SYMPTOMS and use cases
When NOT to use

## Core Pattern (for techniques/patterns)
Before/after code comparison

## Quick Reference
Table or bullets for scanning common operations

## Implementation
Inline code for simple patterns
Link to file for dense reference or reusable tools

## Common Mistakes
What goes wrong + fixes

## Real-World Impact (optional)
Concrete results

Discovery Optimization

Critical for visibility: Future Claude instances must FIND your protocol.

1. Rich Description Field

Purpose: Claude reads the description to decide which protocols to load. Make it answer: "Should I read this protocol right now?"

Format: Start with "Use when..." focusing on trigger conditions.

CRITICAL: Description = When to Use, NOT What the Protocol Does

The description should ONLY describe trigger conditions. Do NOT summarize the protocol's workflow.

Why this matters: Testing revealed that when a description summarizes the workflow, Claude may follow the description instead of reading the full protocol. A description mentioning "review between tasks" caused Claude to perform ONE review, even though the protocol's flowchart clearly showed TWO reviews (spec compliance then code quality).

When the description was changed to just "Use when executing implementation plans with independent tasks" (no workflow summary), Claude correctly read the flowchart and followed the two-stage review process.

The trap: Descriptions that summarize workflow create a shortcut Claude will take. The protocol body becomes documentation Claude skips.

# BAD: Summarizes workflow - Claude may follow this instead of reading protocol
description: Use when executing plans - launches subagent per task with review between tasks

# BAD: Too much process detail
description: Use for TDD - write test first, watch it fail, write minimal code, refactor

# GOOD: Just trigger conditions, no workflow summary
description: Use when executing implementation plans with independent tasks in the current session

# GOOD: Trigger conditions only
description: Use when implementing any feature or bugfix, before writing implementation code

Content:

  • Use concrete triggers, symptoms, and situations that signal this protocol applies
  • Describe the *problem* (race conditions, inconsistent behavior) not *technology-specific symptoms* (setTimeout, sleep)
  • Keep triggers technology-agnostic unless the protocol itself is technology-specific
  • If protocol is technology-specific, make that explicit
  • Write in third person (injected into system prompt)
  • NEVER summarize the protocol's process or workflow
# BAD: Too abstract, vague, no trigger conditions
description: For async testing

# BAD: First person
description: I can help you with async tests when they're flaky

# BAD: Mentions technology but protocol isn't specific to it
description: Use when tests use setTimeout/sleep and are flaky

# GOOD: Starts with "Use when", describes problem, no workflow
description: Use when tests have race conditions, timing dependencies, or pass/fail inconsistently

# GOOD: Technology-specific protocol with explicit trigger
description: Use when using React Router and handling authentication redirects

2. Keyword Coverage

Use words Claude would search for:

  • Error messages: "Hook timed out", "ENOTEMPTY", "race condition"
  • Symptoms: "flaky", "hanging", "zombie", "pollution"
  • Synonyms: "timeout/hang/freeze", "cleanup/teardown/afterEach"
  • Tools: Actual commands, library names, file types

3. Descriptive Naming

Use active voice, verb-first:

  • creating-protocols not protocol-creation
  • event-based-waiting not async-test-helpers

Gerunds (-ing) work well for processes:

  • creating-protocols, validating-protocols, debugging-with-logs
  • Active, describes the action being taken

4. Token Efficiency (Critical)

Problem: Getting-started and frequently-referenced protocols load into EVERY conversation. Every token counts.

Target word counts:

  • Getting-started workflows: <150 words each
  • Frequently-loaded protocols: <200 words total
  • Other protocols: <500 words (still be concise)

Techniques:

Defer details to tool help:

# BAD: Document all flags in SKILL.md
search-conversations supports --text, --both, --after DATE, --before DATE, --limit N

# GOOD: Reference --help
search-conversations supports multiple modes and filters. Run --help for details.

Use cross-references:

# BAD: Repeat workflow details
When searching, dispatch subagent with template...
[20 lines of repeated instructions]

# GOOD: Reference other protocol
Always use subagents (50-100x context savings). REQUIRED: Use [other-protocol-name] for workflow.

Compress examples:

# BAD: Verbose example (42 words)
your human partner: "How did we handle authentication errors in React Router before?"
You: I'll search past conversations for React Router authentication patterns.
[Dispatch subagent with search query: "React Router authentication error handling 401"]

# GOOD: Minimal example (20 words)
Partner: "How did we handle auth errors in React Router?"
You: Searching...
[Dispatch subagent -> synthesis]

Eliminate redundancy:

  • Do not repeat what is in cross-referenced protocols
  • Do not explain what is obvious from the command
  • Do not include multiple examples of the same pattern

Verification:

wc -w skills/path/SKILL.md
# getting-started workflows: aim for <150 each
# Other frequently-loaded: aim for <200 total

Name by what you DO or the core insight:

  • event-based-waiting > async-test-helpers
  • using-protocols not protocol-usage
  • flatten-with-flags > data-structure-refactoring
  • root-cause-tracing > debugging-techniques

5. Cross-Referencing Other Protocols

When writing documentation that references other protocols:

Use protocol name only, with explicit requirement markers:

  • GOOD: **REQUIRED SUB-PROTOCOL:** Use godmode:test-first
  • GOOD: **REQUIRED BACKGROUND:** You MUST understand godmode:fault-diagnosis
  • BAD: See skills/testing/test-first (unclear if required)
  • BAD: @skills/testing/test-first/SKILL.md (force-loads, burns context)

Why no @ links: @ syntax force-loads files immediately, consuming 200k+ context before you need them.

Flowchart Usage

digraph when_flowchart {
    "Need to show information?" [shape=diamond];
    "Decision where I might go wrong?" [shape=diamond];
    "Use markdown" [shape=box];
    "Small inline flowchart" [shape=box];

    "Need to show information?" -> "Decision where I might go wrong?" [label="yes"];
    "Decision where I might go wrong?" -> "Small inline flowchart" [label="yes"];
    "Decision where I might go wrong?" -> "Use markdown" [label="no"];
}

Use flowcharts ONLY for:

  • Non-obvious decision points
  • Process loops where you might terminate too early
  • "When to use A vs B" decisions

Never use flowcharts for:

  • Reference material -> Tables, lists
  • Code examples -> Markdown blocks
  • Linear instructions -> Numbered lists
  • Labels without semantic meaning (step1, helper2)

See graphviz-conventions.dot in this directory for graphviz style rules.

Visualizing for your human partner: Use render-graphs.js in this directory to render a protocol's flowcharts to SVG:

./render-graphs.js ../some-protocol           # Each diagram separately
./render-graphs.js ../some-protocol --combine # All diagrams in one SVG

Code Examples

One outstanding example beats many mediocre ones

Choose the most relevant language:

  • Testing techniques -> TypeScript/JavaScript
  • System debugging -> Shell/Python
  • Data processing -> Python

Strong example:

  • Complete and runnable
  • Well-commented explaining WHY
  • From a real scenario
  • Shows the pattern clearly
  • Ready to adapt (not a generic template)

Avoid:

  • Implementing in 5+ languages
  • Creating fill-in-the-blank templates
  • Writing contrived examples

You are skilled at porting — one strong example is sufficient.

File Organization

Self-Contained Protocol

defense-in-depth/
  SKILL.md    # Everything inline

When: All content fits, no dense reference needed

Protocol with Reusable Tool

event-based-waiting/
  SKILL.md    # Overview + patterns
  example.ts  # Working helpers to adapt

When: Tool is reusable code, not just narrative

Protocol with Dense Reference

pptx/
  SKILL.md       # Overview + workflows
  pptxgenjs.md   # 600 lines API reference
  ooxml.md       # 500 lines XML structure
  scripts/       # Executable tools

When: Reference material too large for inline

The Prime Directive (Same as TDD)

NO PROTOCOL WITHOUT A FAILING TEST FIRST

This applies to NEW protocols AND EDITS to existing protocols.

Author before testing? Delete it. Start over. Edit without testing? Same violation.

No exceptions:

  • Not for "simple additions"
  • Not for "just adding a section"
  • Not for "documentation updates"
  • Do not keep untested changes as "reference"
  • Do not "adapt" while running tests
  • Delete means delete

REQUIRED BACKGROUND: The godmode:test-first protocol explains why this matters. Same principles apply to documentation.

Testing All Protocol Types

Different protocol types require different test approaches:

Discipline-Enforcing Protocols (rules/requirements)

Examples: TDD, completion-gate, design-before-coding

Test with:

  • Academic questions: Do they understand the rules?
  • Pressure scenarios: Do they comply under stress?
  • Multiple pressures combined: time + sunk cost + exhaustion
  • Identify rationalizations and add explicit counters

Success criteria: Agent follows the rule under maximum pressure

Technique Protocols (how-to guides)

Examples: event-based-waiting, root-cause-tracing, defensive-programming

Test with:

  • Application scenarios: Can they apply the technique correctly?
  • Variation scenarios: Do they handle edge cases?
  • Missing information tests: Do the instructions have gaps?

Success criteria: Agent successfully applies technique to a new scenario

Pattern Protocols (mental models)

Examples: reducing-complexity, information-hiding concepts

Test with:

  • Recognition scenarios: Do they recognize when the pattern applies?
  • Application scenarios: Can they use the mental model?
  • Counter-examples: Do they know when NOT to apply?

Success criteria: Agent correctly identifies when and how to apply the pattern

Reference Protocols (documentation/APIs)

Examples: API documentation, command references, library guides

Test with:

  • Retrieval scenarios: Can they find the right information?
  • Application scenarios: Can they use what they found correctly?
  • Gap testing: Are common use cases covered?

Success criteria: Agent finds and correctly applies reference information

Cognitive Traps for Skipping Testing

RationalizationTruth
"Protocol is obviously clear"Clear to you does not mean clear to other agents. Test it.
"It's just a reference"References can have gaps and unclear sections. Test retrieval.
"Testing is overkill"Untested protocols have issues. Always. 15 minutes of testing prevents hours of confusion.
"I'll test if problems surface"Problems mean agents cannot use the protocol. Test BEFORE deploying.
"Too tedious to test"Testing is less tedious than debugging a bad protocol in production.
"I'm confident it's solid"Overconfidence guarantees issues. Test anyway.
"Academic review is sufficient"Reading is not using. Test application scenarios.
"No time to test"Deploying untested protocols wastes more time fixing them later.

All of these mean: Test before deploying. No exceptions.

Hardening Protocols Against Rationalization

Protocols that enforce discipline (like TDD) must resist rationalization. Agents are sophisticated and will discover loopholes under pressure.

Seal Every Loophole Explicitly

Do not just state the rule — forbid specific workarounds:

# Insufficient
Author code before test? Delete it.

# Sufficient
Author code before test? Delete it. Start over.

**No exceptions:**
- Do not keep it as "reference"
- Do not "adapt" it while writing tests
- Do not look at it
- Delete means delete

Preempt "Spirit vs Letter" Arguments

Add a foundational principle early:

**No exceptions. No workarounds. No shortcuts.**

This closes off the entire class of "I'm following the spirit" rationalizations.

Build Rationalization Table

Capture rationalizations from baseline testing. Every excuse agents produce goes in the table:

| Rationalization | Truth |
|-----------------|-------|
| "Too simple to test" | Simple code breaks. Testing takes 30 seconds. |
| "I'll test afterward" | Tests that pass immediately prove nothing about design. |
| "Tests-after achieve the same result" | Tests-after = "what does this do?" Tests-first = "what should this do?" |

Create Guardrails List

Make it easy for agents to self-check when rationalizing:

## Guardrails - HALT and Start Over

- Code before test
- "I already manually tested it"
- "Tests after achieve the same purpose"
- "It's about spirit not ritual"
- "This is different because..."

**All of these mean: Delete code. Start over with TDD.**

Update Description for Violation Symptoms

Add to description: symptoms of when you are ABOUT to violate the rule:

description: Use when implementing any feature or bugfix, before writing implementation code

RED-GREEN-REFACTOR for Protocols

Follow the TDD cycle:

RED: Write Failing Test (Baseline)

Run a pressure scenario with a subagent WITHOUT the protocol. Document exact behavior:

  • What choices did they make?
  • What rationalizations did they use (verbatim)?
  • Which pressures triggered violations?

This is "watch the test fail" — you must observe what agents naturally do before authoring the protocol.

GREEN: Author Minimal Protocol

Author a protocol that addresses those specific rationalizations. Do not add content for hypothetical cases.

Run the same scenarios WITH the protocol. The agent should now comply.

REFACTOR: Seal Loopholes

Agent found a new rationalization? Add an explicit counter. Re-test until airtight.

Testing methodology: See @testing-skills-with-subagents.md for the complete testing methodology:

  • How to design pressure scenarios
  • Pressure categories (time, sunk cost, authority, exhaustion)
  • Systematic hole-plugging
  • Meta-testing techniques

Anti-Patterns

Narrative Example

"In session 2025-10-03, we found empty projectDir caused..." Why bad: Too specific, not reusable

Multi-Language Dilution

example-js.js, example-py.py, example-go.go Why bad: Mediocre quality, maintenance burden

Code in Flowcharts

step1 [label="import fs"];
step2 [label="read file"];

Why bad: Cannot copy-paste, hard to read

Generic Labels

helper1, helper2, step3, pattern4 Why bad: Labels should carry semantic meaning

STOP: Before Moving to Next Protocol

After authoring ANY protocol, you MUST STOP and complete the deployment process.

Do NOT:

  • Create multiple protocols in batch without testing each
  • Move to the next protocol before the current one is verified
  • Skip testing because "batching is more efficient"

The deployment checklist below is MANDATORY for EACH protocol.

Deploying untested protocols = deploying untested code. It violates quality standards.

Protocol Creation Checklist (TDD Adapted)

RED Phase - Write Failing Test:

  • Create pressure scenarios (3+ combined pressures for discipline protocols)
  • Run scenarios WITHOUT protocol - document baseline behavior verbatim
  • Identify patterns in rationalizations and failures

GREEN Phase - Author Minimal Protocol:

  • Name uses only letters, numbers, hyphens (no parentheses or special chars)
  • YAML frontmatter with only name and description (max 1024 chars)
  • Description starts with "Use when..." and includes specific triggers/symptoms
  • Description written in third person
  • Keywords throughout for discoverability (errors, symptoms, tools)
  • Clear overview with core principle
  • Address specific baseline failures identified in RED
  • Code inline OR link to separate file
  • One outstanding example (not multi-language)
  • Run scenarios WITH protocol - verify agents now comply

REFACTOR Phase - Seal Loopholes:

  • Identify NEW rationalizations from testing
  • Add explicit counters (if discipline protocol)
  • Build rationalization table from all test iterations
  • Create guardrails list
  • Re-test until airtight

Quality Checks:

  • Small flowchart only if decision non-obvious
  • Quick reference table
  • Common mistakes section
  • No narrative storytelling
  • Supporting files only for tools or dense reference

Deployment:

  • Commit protocol to git and push to your fork (if configured)
  • Consider contributing back via PR (if broadly useful)

Discovery Workflow

How future Claude discovers your protocol:

  1. Encounters problem ("tests are flaky")
  2. Finds PROTOCOL (description matches)
  3. Scans overview (is this relevant?)
  4. Reads patterns (quick reference table)
  5. Loads example (only when implementing)

Optimize for this flow — put searchable terms early and often.

The Bottom Line

Creating protocols IS TDD for process documentation.

Same Prime Directive: No protocol without failing test first. Same cycle: RED (baseline) -> GREEN (author protocol) -> REFACTOR (seal loopholes). Same benefits: Higher quality, fewer surprises, airtight results.

If you follow TDD for code, follow it for protocols. It is the same discipline applied to documentation.

平台分布

Codex

35.09%
按下载量换算31

Claude

30.29%
按下载量换算26

Cursor

21.31%
按下载量换算19

Gemini CLI

9.4%
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

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。

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