skill-content-fit

skill-content-fit is a skill for Codex from tranfu-labs/tranfu-skills. It costs 160 tokens per session (1,926 once invoked), scanned A, original, MIT.

A checklist for deciding whether project knowledge or lessons learned are suitable for packaging as a reusable coding-agent skill. It checks for repeatable triggers, steps, tools, verification, and boundaries.

In plain words
What is it for?
Use it before creating a new skill from a project document, incident review, guardrail, or process note.
Why use it?
It prevents one-off notes, vague advice, or isolated facts from being turned into skills that agents cannot reliably use.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it before creating a new skill from a project document, incident review, guardrail, or process note.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tranfu-labs/tranfu-skills/skill-content-fit
Install

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.

Any agent
npx skills add tranfu-labs/tranfu-skills --skill skill-content-fit
Clone the repo
git clone --depth 1 https://github.com/tranfu-labs/tranfu-skills

Made for: Codex.

Wrote 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.

agentmods badge for skill-content-fit

README.md
[![agentmods](https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/skill-content-fit/github.svg)](https://agentmods.dev/skills/tranfu-labs/tranfu-skills/skill-content-fit)
Your own site
<a href="https://agentmods.dev/skills/tranfu-labs/tranfu-skills/skill-content-fit"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/skill-content-fit/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.

agentmods 80×15 button for skill-content-fit

Your own site · 80×15
<a href="https://agentmods.dev/skills/tranfu-labs/tranfu-skills/skill-content-fit"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/skill-content-fit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 160 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,926 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00160 $0.01926
Opus 5 $0.00080 $0.00963
Sonnet 5 $0.00032 $0.00385
Haiku 4.5 $0.00016 $0.00193

Measured 9d ago against content hash 8bcd747f124f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

skill-content-fit scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

所有 social preview 图片必须是绝对 HTTPS URL,未登录可访问,返回 200 和正确 Content-Type;Lark 目标场景必须用生产 URL 实测。触发于发布前检查 Open Graph/Twitter/Lark 预览图。流程:1. 提取页面 meta 图片 URL;2. 用未登录环境请求图片;3. 检查状态码和 Content-Type;4. 在 Lark 生产链接里实测预览。反例:只修某一次 CDN 配
own-skills/skill-content-fit/SKILL.md · 162 lines

How it starts

The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.

什么内容适合写成 Skill

职责边界

这个 skill 只做一件事:判断给定内容是否够格写成 Codex skill。

输出只有两类:

  • 通过:内容满足 skill 准入要求,可以进入 skill 命名、边界框定和编写阶段。
  • 打回:内容暂时不符合 skill 准入要求,必须补齐缺口后再评估。

NEVER 替不合格内容决定去向。MUST 只说明为什么不适合写成 skill,以及要补什么,unless the user explicitly asks for alternatives.

核心判断

skill 不是知识仓库,而是可重复执行能力。

有误差只是触发学习的信号,不等于一定要创建 skill:

误差 = 发现偏差
skill = 把可重复、可复用的纠偏方法固化下来

只有当某类误差背后暴露的是“可重复改进的流程问题”时,才值得写成 skill。

准入标准

CRITICAL: 结论为“通过”时,MUST 满足 6/6 项准入标准。每一项都 MUST 能从输入材料中摘出或指向至少 1 条证据;不能靠 agent 临场补写。

  1. 可重复:能指出未来还会遇到的任务类型、误差类型或高风险场景;不是只描述单次事实。
  2. 有触发:包含至少 1 个用户话术、文件类型、任务场景或失败模式。
  3. 有流程:包含至少 3 个有序步骤,或 1 个有分支条件的决策树,或 1 份可逐项勾选的检查清单。
  4. 可执行:agent 能按材料采取行动;必要工具、脚本、模板、命令或人工动作至少出现 1 类。
  5. 可验证:包含至少 1 种验收方式,例如命令退出码、测试结果、文件/字段存在性、产物检查、人工确认人或明确通过标准。
  6. 有边界:包含至少 1 条反例、排除项、停止条件或“不该使用”的场景。

高风险或高代价场景可以降低重复次数要求,但 NEVER 降低流程和验证要求。法务、财务、医疗、安全、合规、生产发布等内容即使只出现一次,也 MUST 有稳定步骤和验收方式,才通过。

打回标准

出现任一情况时打回:

  • 只是项目当前状态、背景说明、roadmap 或一次性事实。
  • 只是事故流水账,尚未提炼出可复用纠偏流程。
  • 只是用户临时偏好、情绪、上下文或单次指令。
  • 只是单个知识点,例如某个语言特性、API 事实或术语解释。
  • 只是不可执行、不可验证的价值判断。
  • 只是“写得更好”“减少错误”“提升质量”这类过宽目标。
  • 只是工具或代码 bug 的现象描述,没有可复用修复流程。
  • 只有结论,没有触发条件、步骤、反例或验收标准。
  • 触发场景过窄,未来很难再次遇到。
  • 需要读者记住某次事故里的专有名词、文件位置或排障路径才知道怎么用。

NEVER 为打回内容补写假流程。MUST 只列出输入中缺失的字段和需要用户补充的信息,unless the user explicitly asks you to draft a candidate workflow.

评估流程

CREATE A TODO LIST FOR THE TASKS BELOW,并按 1-5 步逐项检查:

  1. 识别这段内容想沉淀什么能力:任务执行、错误纠偏、质量检查、产物生成、排障流程,还是只是事实记录。
  2. 如果来自误差或事故,先问:这是一次性偏差,还是可重复的流程问题?
  3. 检查六个准入标准:可重复、触发、流程、可执行、可验证、有边界。
  4. 任一硬条件缺失就打回,并列出必须补齐的最小信息。
  5. 全部满足才通过;通过后再进入 skill 命名、边界框定和编写阶段。

输出模板

结论: 通过 / 打回

判断:
- 可重复:
- 触发条件:
- 可执行流程:
- 验证方式:
- 边界和反例:

如果打回:
- 缺失项:
- 需要补充:

如果通过:
- 建议提炼为 skill 的内容:
  - 触发条件:
  - 工作流:
  - 反例:
  - 验收标准:

示例

输入:

2026-05-28 首页在 Lark 里没有显示预览图,因为 CDN 对图片返回了错误 Content-Type。

输出:

结论: 打回

判断:
- 可重复: 未提供未来会重复出现的任务类型或误差类型。
- 触发条件: 未提供用户话术、文件类型、任务场景或失败模式。
- 可执行流程: 只有事件结果,没有步骤、决策树或检查清单。
- 验证方式: 未提供命令、产物检查、人工验收或明确通过标准。
- 边界和反例: 未提供不该使用的场景。

如果打回:
- 缺失项: 触发条件、可执行流程、验证方式、边界和反例。
- 需要补充: 未来在哪类 social preview 任务中触发、按什么顺序检查 URL/权限/Content-Type、如何验收、哪些情况不适合写成 skill。

Read the full file on GitHub · 162 lines

Files

What ships with it

5 files 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.

Changes

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.

  1. 9d ago First seen · 162 lines · 160 tokens per session scan A 8bcd747f124f

Subscribe to this mod's changes

skill-content-fit is a skill published in the GitHub repository tranfu-labs/tranfu-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 160 tokens to every session and 1,926 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens