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 flanliulf/SpecLite --skill speclite-editorial-review-structuregit clone --depth 1 https://github.com/flanliulf/SpecLiteWrote 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/flanliulf/speclite/speclite-editorial-review-structure)<a href="https://agentmods.dev/skills/flanliulf/speclite/speclite-editorial-review-structure"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-editorial-review-structure/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/flanliulf/speclite/speclite-editorial-review-structure"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-editorial-review-structure.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 | $0.00074 | $0.00569 |
| Opus 5 | $0.00037 | $0.00284 |
| Sonnet 5 | $0.00015 | $0.00114 |
| Haiku 4.5 | $0.00007 | $0.00057 |
Grade A, and why
speclite-editorial-review-structure 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 11d 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
[技能说明] Speclite Editorial Review Structure 是结构编辑器，在 copy editing 前审查文档结构，提出裁剪、合并、移动、浓缩、问题和保留建议。它关注高价值密度，同时保留理解所需的结构和辅助信息。
[核心能力]
- 输入校验：确认 content 至少 3 个词，reader_type 为 humans 或 llm。
- 目的建模：推断或读取 purpose、target_audience、reader_type 和 length_target。
- 结构模型选择：在 Tutorial/Guide、Reference、Explanation、Prompt/Task、Strategic/Context 中选择适配模型。
- 结构分析：映射章节、字数、服务目的程度、冗余和 scope violation。
- 流动性分析：识别 premature detail、missing scaffolding、burying 和 pacing 问题。
- 建议输出：按 CUT/MERGE/MOVE/CONDENSE/QUESTION/PRESERVE 输出优先级建议。
[执行流程]
1. 校验 content 和 reader_type；无效时 HALT。
2. 推断或读取文档 purpose、target_audience 和 reader_type。
3. 选择最合适的 structure model，并说明文档存在目的。
4. 如提供 style_guide，先读取并作为最高优先级规则。
5. 映射文档结构，逐节评估服务目的、冗余、scope、埋藏信息和 flow。
6. 输出 Document Summary、Recommendations 和 Summary。
7. 如无结构问题，输出 No substantive changes recommended。
[注意事项]
- CONTENT IS SACROSANCT：绝不挑战观点，只优化组织方式。
- 建议而不执行，用户决定是否接受。
- human reader 的图表、例子、概览和 callout 可能服务理解，不应机械删除。
- reader_type 为 llm 时优先精确、明确和一致术语。
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.
- 11d ago First seen · 37 lines · 74 tokens per session scan A acba700da49f
speclite-editorial-review-structure is a skill published in the GitHub repository flanliulf/SpecLite (4 stars, last pushed 2mo ago), licensed MIT. It adds 74 tokens to every session and 569 once invoked, about $0.0004 per session on Opus 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
lain
Structural code intelligence for AI coding agents. Use this skill when the user wants to understand how a codebase is organized (modules, call graphs, file dependencies), find where to start reading, trace the impact of a change, find code by meaning, or understand what a symbol does in its full context. Do NOT use…
botpipe-workflow-authoring
Author, review, and improve Botpipe workflows. Use when Codex is asked to create packaged or workspace-local Botpipe workflows, convert codebases into workflows, design provider-heavy producer/verifier steps, write Botpipe prompts/contracts, inspect Botpipe traces, or apply Codex CLI/gpt-5.5 workflow patterns.
pre-merge
The CI gate. Takes a feature branch from "eng says done" to "PR open against staging with green checks". Runs the project's preflight-resolved pipeline from devkit/policy.json components[]: sync → parallel correctness + security waves → coverage → regression tail → security/migration → PRD-consistency → open PR. Emits…
intake
The planning front-door. Captures feature ideas and bugs as graded rows in the root INTAKE.md ledger. Use it when the user says "log an idea", "capture a bug", "add to the backlog", "note this down", "track this feature", or invokes /intake. Owns the requirements interview — fleshes out thin ideas, proactively…
merge
The ship gate — the only skill that merges. --staging merges the feature→staging PR on green CI, deploys, verifies, emits a human test script and stamps the staging sign-off on approval. --production ships the double-confirmed release to main and deploys production. Never self-certifies staging; nothing reaches main…
msg
Root menu for msg skills, plus harness modes. --init is the one-time project bootstrap — use it when the user says "initialise project", "bootstrap repo", "set up the framework", "start a new project", or asks to set up project structure in an empty repo. Other modes: --init-staging (add a staging branch), --update…