Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add DongLiStudio/personal-agent-foundation --skill record-skill-dependencygit clone --depth 1 https://github.com/DongLiStudio/personal-agent-foundationWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/donglistudio/personal-agent-foundation/record-skill-dependency)<a href="https://agentmods.dev/skills/donglistudio/personal-agent-foundation/record-skill-dependency"><img src="https://agentmods.dev/badge/skills/donglistudio/personal-agent-foundation/record-skill-dependency/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/donglistudio/personal-agent-foundation/record-skill-dependency"><img src="https://agentmods.dev/badge/skills/donglistudio/personal-agent-foundation/record-skill-dependency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00109 | $0.01021 |
| Opus 5 | $0.00055 | $0.00511 |
| Sonnet 5 | $0.00022 | $0.00204 |
| Haiku 4.5 | $0.00011 | $0.00102 |
Grade A, and why
record-skill-dependency scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
83% identical to luban — 536 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
记录 Skill 依赖
使用这个 Skill 在新增、安装或同步全局 Skill 后,维护 GLOBAL/SKILL_DEPENDENCIES.md。
核心规则
源稿位于 {{AGENT_ROOT}}\GLOBAL\.agents\skills\ 的自维护全局 Skill 必须记录,并保持源稿、用户级安装副本和依赖清单一致。
外部 Skill 只记录用户主动安装、且迁移或重装环境时需要主动恢复的条目。
外部 Skill 如果缺少配套 CLI、桌面应用、运行时、系统能力或授权就无法工作,必须同时记录该运行依赖、恢复步骤和最小验证命令;不能只记录 SKILL.md 的安装方式。
记录:
- 用户自己维护、并需要跨项目全局使用的 Skill。
- 用户主动从外部来源安装的 Skill。
- 依赖某个外部仓库、插件或手动步骤才能恢复的 Skill。
- 对长期工作流有稳定影响,换电脑时必须主动恢复的 Skill。
不记录:
- 默认预装 Skill。
- 系统 Skill。
- 插件随安装自动提供的 Skill。
- 插件缓存路径中的 Skill。
- 项目专属 Skill。
- 当前会话或运行时临时产物。
工作流程
- 判断本次对象是 GLOBAL 自维护 Skill、主动安装的外部 Skill、项目专属 Skill,还是默认/插件/缓存/临时内容。
- 如果是默认预装、系统、插件提供、插件缓存、项目专属 Skill 或临时产物,说明原因并停止,不要污染依赖清单。
- 如果是 GLOBAL 自维护 Skill,必须记录或更新。
- 如果是用户主动安装的外部 Skill,确认它是否需要迁移或重装时主动恢复;需要则记录,不需要则说明原因并停止。
- 判断该 Skill 是否依赖额外 CLI、应用、运行时、系统能力或授权;存在必需依赖时,记录恢复步骤和不产生业务写入的最小验证命令。
- 读取
GLOBAL/SKILL_DEPENDENCIES.md。 - 判断应该写入哪个章节:
GLOBAL 自维护 Skill:源稿在{{AGENT_ROOT}}\GLOBAL\.agents\skills\的个人全局 Skill。主动安装的外部 Skill:用户从外部来源主动安装、但源稿不由 GLOBAL 维护的 Skill。
- 如果条目已存在,更新恢复方式、来源、运行依赖或用途;不要重复添加。
- 如果
主动安装的外部 Skill当前为“暂无。”,新增第一条外部 Skill 时移除“暂无。”。 - 保持条目简短、事实化,优先记录恢复所需信息,而不是复制 Skill 内容。
- 结束时说明记录到了哪个章节,以及是否跳过了默认预装/插件 Skill。
条目格式
GLOBAL 自维护 Skill:
### `skill-name`
- 源稿:`{{AGENT_ROOT}}\GLOBAL\.agents\skills\skill-name`
- 恢复方式:从 GLOBAL 源稿安装或同步到当前 Agent 可发现的全局 Skill 位置。
- 用途:一句话说明用途。
主动安装的外部 Skill:
### `skill-name`
- 来源:外部仓库、安装命令、插件或其他可恢复来源。
- 恢复方式:重新执行安装命令,或按来源说明恢复;安装到当前 Agent 可发现的全局 Skill 位置。
- 运行依赖:仅在缺少配套 CLI、应用、运行时、系统能力或授权会导致 Skill 不可用时记录,并附最小只读验证命令。
- 用途:一句话说明用途。
安全边界
不要复制系统 Skill、插件 Skill 或缓存目录内容到 GLOBAL。
不要递归移动、复制或删除 Junction / symlink 指向内容。
如果缺少来源、用途或恢复方式,先尽量从当前安装目录、用户说明或相关文档判断;仍不清楚时,只问必要问题。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 80 lines · 109 tokens per session scan A 8c2b7582b311
record-skill-dependency is a skill published in the GitHub repository DongLiStudio/personal-agent-foundation (11 stars, last pushed 22d ago), licensed Apache-2.0. It adds 109 tokens to every session and 1,021 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to luban, differing in 536 lines, and is treated as a copy.
Other skills, from other repositories
harbor-daytona
Use Harbor's Daytona sandbox platform for computer use — creating sandboxes, taking screenshots, sending mouse/keyboard input, and building agent loops. Use when the user wants to interact with a GUI, automate a desktop, do computer use, control a browser visually, or run Claude computer use against a Daytona sandbox.
boost-modules
Skill "boost-modules" from av/harbor, covering harbor boost custom modules, module structure, quick reference, output methods and stream text to client.
token-usage
Nested swiss-knife reference for token usage, cost, cache, and tool-call/API-call reports. Use for model cost reports, cache rates, budget/burn analysis, and tools-per-API-call trends across LingTai logs.
security-arsenal
Security payloads, bypass tables, wordlists, gf pattern names, always-rejected bug list, and conditionally-valid-with-chain table. Use when you need specific payloads for XSS/SSRF/SQLi/XXE/NoSQLi/command injection/SSTI/IDOR/path-traversal/HTTP smuggling/WebSocket/MFA bypass, bypass techniques, or to check if a finding…
langgraph
LangGraph 1.x (LTS) Python workflow patterns for state management, delta channels, resilience (node timeouts, error handlers, graceful drain), routing, parallel execution, supervisor-worker, tool calling, checkpointing, human-in-loop, streaming (v2 format), subgraphs, and functional API. Use when building LangGraph…
lc-curate-context
Decide which files a task actually needs, record that as a reusable llm-context rule, verify it against the codebase - including the files your selection references but leaves out - and pack it for your own context, a chat, or a sub-agent you dispatch. Load when choosing what code to put in front of a model, packing…