Borrowing it
Nothing to install: this file belongs to lisitan/writing-team-workbench. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lisitan/writing-team-workbench/main/.claude/skills/00-topic-inbox/SKILL.mdgit clone --depth 1 https://github.com/lisitan/writing-team-workbenchWrote 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/lisitan/writing-team-workbench/00-topic-inbox)<a href="https://agentmods.dev/skills/lisitan/writing-team-workbench/00-topic-inbox"><img src="https://agentmods.dev/badge/skills/lisitan/writing-team-workbench/00-topic-inbox/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/lisitan/writing-team-workbench/00-topic-inbox"><img src="https://agentmods.dev/badge/skills/lisitan/writing-team-workbench/00-topic-inbox.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00673 |
| Opus 5 | $0.00000 | $0.00336 |
| Sonnet 5 | $0.00000 | $0.00135 |
| Haiku 4.5 | $0.00000 | $0.00067 |
Grade A, and why
00-topic-inbox 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 10d 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
00-topic-inbox
把灵感整理成可进入连续生产系统的候选选题。
适用场景
- 用户只有一句想法、一个标题、一个评论反馈或一段素材。
- 还不确定是否值得创建文章项目。
- 需要把灵感放入
05-资产/选题池.md,以后再处理。
角色目标
把模糊输入压缩成可判断、可立项、可检索的候选选题。
资料源
- 必读:
05-资产/选题池.md - 可读:
05-资产/素材库.md - 可查:个人笔记库中的历史想法、相似选题、旧判断
- 默认不联网;只有判断外部趋势或语境时才联网
可用能力
- 灵感清洗:把口语化、碎片化输入改成一个候选选题。
- 重复检查:检查选题池里是否已有相似选题。
- 历史召回:用
personal-notes-readonly.personal_notes_recall查相似想法和素材线索。 - 体裁初判:在观点文、复盘文、方法文中给出推荐。
- 读者任务识别:写清目标读者、核心问题和读者任务。
- 入池记录:把候选选题追加到
05-资产/选题池.md。
执行步骤
- 读取
05-资产/选题池.md和用户输入。 - 检查是否已有重复或相似选题。
- 必要时通过
personal_notes_recall查个人笔记库;未配置时标注“个人笔记库未配置,未检索”。 - 判断体裁和目标读者。
- 写出核心问题、核心判断和素材线索。
- 追加到
05-资产/选题池.md,状态默认为候选。
输出文件
05-资产/选题池.md
记录格式
## 选题:标题
- 状态:候选
- 体裁:观点文 / 复盘文 / 方法文
- 目标读者:
- 读者任务:
- 核心问题:
- 核心判断:
- 素材线索:
- 项目链接:
- 下一步:
质量检查
- 选题不是宽泛主题,而是一个可写的问题。
- 有具体目标读者和读者任务。
- 核心判断可以被反驳。
- 素材线索注明来自项目、本地素材库或个人笔记库。
- 不把个人笔记库内容伪装成外部事实。
禁止事项
- 不创建项目。
- 不写完整正文。
- 不向远端个人笔记库写入、修改或删除内容。
- 不调用个人笔记库的写入、更新、删除、标签、分享或上传工具。
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.
- 10d ago First seen · 76 lines · 0 tokens per session scan A feabc36e1f01
00-topic-inbox is a skill published in the GitHub repository lisitan/writing-team-workbench (20 stars, last pushed 25d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 673 tokens. 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
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…
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…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…