Agent 生成器
- 作者仓库星标 290
- 作者更新于 实时读取
- 作者仓库 communitytools
- 领域
- 工程开发
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @transilienceai · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- 无特殊要求
- 文件与系统权限
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- 只读
- 允许写入 / 修改
- Shell 执行
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: skill-update
description: Skill creation, update and management — generates skill directory structure, validates against b…
category: 工程开发
runtime: 无特殊运行时
---
# skill-update 输出预览
## PART A: 任务判断
- 适用问题:代码实现、重构、调试或代码审查。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Hard caps (enforced by scripts/skilllinter.py) / Principles / File structure”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于代码实现、重构、调试或代码审查,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Hard caps (enforced by scripts/skilllinter.py) / Principles / File structure”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令。
先用一个小任务确认它会围绕“Hard caps (enforced by scripts/skilllinter.py) / Principles / File structure”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: skill-update
description: Skill creation, update and management — generates skill directory structure, validates against b…
category: 工程开发
source: transilienceai/communitytools
---
# skill-update
## 什么时候使用
- 把工程方向的常用动作沉淀成 Agent 可调用的技能 适合处理工程开发场景下的代码实现、调试、重构、测试或代码审查,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代…
- 面向代码实现、重构、调试或代码审查,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Hard caps (enforced by scripts/skilllinter.py) / Principles / File structure」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "skill-update" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Hard caps (enforced by scripts/skilllinter.py) / Principles / File structure
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件、执行终端命令 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Skill Update
Generate or refine Claude Code skills following Anthropic best practices.
Hard caps (enforced by scripts/skill_linter.py)
SKILL.md≤ 150 linesreference/*.md≤ 200 lines (reference/scenarios/*.md≤ 400 lines)README.md≤ 100 lines- Every
SKILL.mdhas YAML frontmatter withname+description - No
DO NOT/MUST NOT/NEVERoutside an## Anti-Patternssection - No challenge-specific identifiers (machine names, lab IDs, lab IPs, preserved flags)
- Every Markdown link resolves to an existing file
- Every reference file is linked from at least one other file (no orphans)
Principles
- Brevity first. Every file short, simple, human-readable. Challenge every token.
- Progressive disclosure. SKILL.md navigates;
reference/holds detail;reference/scenarios/holds concrete exploit flows. - Separation of concern. SKILL.md = WHAT + when.
reference/role-*.md= HOW agents behave when spawned. - Single canonical home for any cross-cutting rule (output discipline, credential loading, brute-force, etc.). Other files reference, never restate.
File structure
skills/<skill-name>/
├── SKILL.md # ≤150 lines, YAML + navigation
├── reference/
│ ├── *-principles.md # ≤150 lines (decision tree)
│ ├── INDEX.md
│ ├── *.md # patterns, ≤200 lines
│ └── scenarios/
│ └── <category>/
│ └── *.md # ≤400 lines, self-contained
└── README.md # optional, ≤100 lines
SKILL.md template
---
name: <skill-name>
description: What it does AND when to use. Include trigger phrases.
---
# <Skill Name>
<one-paragraph scope>
## When to use
- <bullet>
## Workflow / Quick start
<≤30 lines>
## References
- [reference/...](reference/...)
## Anti-Patterns
- <when negative framing is genuinely needed, put it here>
When to update an existing skill
Process the techniques and failure modes from completed engagements. Promote a learning to the skill base only if all four hold:
- Generalizable. Reusable pattern, not target-specific lore. No machine names, lab IDs, target IPs, preserved flags, writeup attributions.
- Material improvement. Adds coverage, efficiency, or decision-quality for future engagements.
- Not already captured elsewhere in the skill base. (
scripts/skill_linter.pyflags duplicates.) - Minimal footprint. Prefer extending an existing entry over adding a new file. Keep the base lean and high-signal.
Reframing recipe
Always frame as a reusable pattern: "when encountering X condition, try Y approach" — never "on box-N, Y worked". Use <TARGET_IP>, <DC_FQDN>, <DOMAIN> placeholders in tool examples.
Pre-write check
Before writing, run python3 scripts/skill_linter.py. Reject any change that:
- Re-introduces challenge-specific lore.
- Pushes a
SKILL.mdpast 150 or a reference past its cap. - Duplicates a single-owner rule (brute-force, output discipline, env-reader).
- Adds
DO NOT/MUST NOT/NEVERoutside an Anti-Patterns block.
Output
Concise change report:
- Updated. File + one-line summary of edit.
- Skipped. Notable findings intentionally not added, with brief reasoning.
- No changes. State explicitly when nothing warranted an update.
Reference
- STRUCTURE.md — directory layout requirements.
- FRONTMATTER.md — YAML rules.
- CONTENT.md — writing guidelines.
Anti-Patterns
- Creating CHANGELOG.md / SUMMARY.md / VERIFICATION.md auxiliary files.
- Meta-documentation about the creation process inside the skill itself.
- Verbose inline templates and examples (link to
reference/instead). - Re-introducing duplicate rule prose (brute-force, output-dir, env-reader).
- Files past their cap — split into
reference/immediately.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核