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 xyy277/doc77 --skill doc-lintgit clone --depth 1 https://github.com/xyy277/doc77Wrote 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/xyy277/doc77/doc-lint)<a href="https://agentmods.dev/skills/xyy277/doc77/doc-lint"><img src="https://agentmods.dev/badge/skills/xyy277/doc77/doc-lint/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/xyy277/doc77/doc-lint"><img src="https://agentmods.dev/badge/skills/xyy277/doc77/doc-lint.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 | $0.00039 | $0.00343 |
| Opus 5.5 | $0.00016 | $0.00137 |
| Sonnet 5.5 | $0.00008 | $0.00069 |
| Haiku 4.5 | $0.00004 | $0.00034 |
Grade A, and why
doc-lint 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 1mo 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.
What it actually says
文档规范检查技能
检查项目
格式规范
- Markdown 标题层级是否连续（不跳级）
- 列表缩进是否一致（2 空格或 4 空格）
- 代码块是否有语言标注
- 表格格式是否正确
- 空行：标题前后各一空行，列表项之间不留空行
链接检查
- 内部链接指向的文件是否存在
- 锚点链接格式是否正确（小写、连字符分隔）
- 外部 URL 格式是否合法
术语一致性
- 同一概念是否全文使用统一译法
- 缩写首次出现是否给出全称
- 中英文混排时中英文之间是否有空格
拼写和语法
- 常见拼写错误检测
- 标点符号：中文用全角，英文用半角
- 句末标点是否一致
输出格式
按严重程度分级：
- 🔴 错误：必须修复（格式错误、断链）
- 🟡 警告：建议修复（不一致、不规范）
- 🔵 提示：可选优化（风格建议）
每条包含：文件路径、行号、问题描述、修复建议。
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.
- 1mo ago First seen · 42 lines · 39 tokens per session scan A d7ca4f9a7dda
doc-lint is a skill published in the GitHub repository xyy277/doc77 (8 stars, last pushed 10d ago), licensed MIT. It adds 39 tokens to every session and 343 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
llmwiki
Build and use a persistent, citation-traceable knowledge wiki from documents, research papers, notes, or project documentation. Use for llmwiki projects, retrieving reusable evidence for an agent task, or compiling a corpus for repeated questions. A one-off file read or live web search does not need a wiki.
gwm
Manage git worktrees across any repository with the gwm Rust binary (CLI + ratatui TUI). Use when the user asks to create / list / remove / bootstrap / switch / link worktrees, run a command across worktrees (gwm exec) or reclaim build artifacts (gwm clean), materialise a PR into a worktree (gwm review), drive a…
handoff
Hand work to another tool, account or machine and pick it up there, in two words. Use when the user says "hand off", "hand off all", "out of tokens", "switching accounts", "pick up" or "continue".
sw-do
Work a SpecWeave increment task by task - claim, implement inside its Files, test, commit, done with evidence - alone, unattended or in lanes, then close. Use for "implement", "continue", "auto".
review
Adversarial review of an increment before it ships, by a fresh context or another model family; every finding cites path:line and is re-verified. Use for "review", "qa", "critique this".
glossary
Build the shared language - interview the user term by term and write GLOSSARY.md with what each term means in the business, the data, the code and the UI. Use for "glossary", "ubiquitous language".