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 agentmods add skills/double-coding-lab/flow2spec/f2s-req-clarifynpx skills add double-coding-lab/Flow2Spec --skill f2s-req-clarifygit clone --depth 1 https://github.com/double-coding-lab/Flow2SpecWhat 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 | $0.00045 | $0.00919 |
| Opus 5 | $0.00023 | $0.00460 |
| Sonnet 5 | $0.00009 | $0.00184 |
| Haiku 4.5 | $0.00005 | $0.00092 |
Grade A, and why
f2s-req-clarify 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 2d 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
编排(主 / 子 agent)
subAgent/switchAgentVerification两字段语义以统一入口为唯一事实源:Cursor/Claude 读配置根rules/f2s-flow2spec-unified-entry.*;Codex 读.codex/topics/f2s-flow2spec-unified-entry.md(与上同源,flow2spec init镜像)。本技能不复述。- 本技能默认不拆子:无论
subAgent真值,澄清流程全程在主会话进行(追问与用户对齐强依赖连续同会话,拆子必断上下文)。 - 校验口径为落盘侧自验,本技能不绑定交叉校验。
需求澄清
执行口径:澄清文档统一落盘到
.Knowledge/req-docs/。
入参:可选。PRD 全文、需求描述或文档路径(如 .Knowledge/req-docs/xxx.md);不传则按当前对话内容澄清。后续回复可补需求条件。
行为:找出需求中的模糊表述、未定义概念、缺失信息、矛盾、与实现相关但未说明的点 → 分组、具体可答地反问 → 根据回答迭代追问,直到流程、边界、异常、关键概念无歧义。不替用户做业务假设,不清楚就问。
结束(澄清文档落盘 → 自动衔接技术方案):当信息已足够清晰时,必须输出一份可直接落盘的「需求澄清文档」(Markdown)。文档至少包含:背景与目标、范围(包含/不包含)、关键流程、边界与异常、关键概念定义、验收标准、未决问题(如有)。建议保存到 .Knowledge/req-docs/(推荐命名 <能力名>_需求澄清.md)。
澄清文档落盘后本技能同轮自动衔接 f2s-req-tech:以刚落盘的澄清文档路径为输入直接进入技术方案生成,无需等用户再次触发;进入前给用户一行提示「澄清文档已就绪:<路径>;正在按 f2s-req-tech 生成技术方案」,然后继续。
例外——停在澄清、不自动衔接技术方案(任一命中即停):
- 澄清文档「未决问题」小节仍有影响方案结构的关键项未回答(如库/表/接口/状态机主契约缺定义),此时输出一段说明列出待答项,等用户回答后再落盘并衔接;
- 用户在澄清过程中明确说「先只出澄清 / 别急着做方案 / 先讨论」等停步语;
- 用户显式指定了不同的后续动作(如「澄清完就停」「先给我拆任务」)。
禁止:
- 在澄清文档尾部或紧随其后追加
f2s-kb-distill收口提示(见rules/f2s-kb-feedback-closing.*禁止段——过程编排型技能落盘不触发 distill); - 未落盘澄清文档就自动衔接
f2s-req-tech(自动衔接的前提是磁盘上已有澄清文档路径); - 越级自动衔接
f2s-req-plan/implement-tech-design/ 其他f2s-*技能(同轮只允许接到f2s-req-tech一步,后续仍须用户新一轮触发)。
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.
- 2d ago First seen · 33 lines · 45 tokens per session scan A 83543d5bfbdd
f2s-req-clarify is a skill published in the GitHub repository double-coding-lab/Flow2Spec (47 stars, last pushed 5d ago), licensed MIT. It adds 45 tokens to every session and 919 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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.
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…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.