Borrowing it
Nothing to install: this file belongs to double-coding-lab/Flow2Spec. 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/double-coding-lab/Flow2Spec/main/.claude/skills/f2s-kb-addRules/SKILL.mdgit clone --depth 1 https://github.com/double-coding-lab/Flow2SpecWrote 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/double-coding-lab/flow2spec/f2s-kb-addrules)<a href="https://agentmods.dev/skills/double-coding-lab/flow2spec/f2s-kb-addrules"><img src="https://agentmods.dev/badge/skills/double-coding-lab/flow2spec/f2s-kb-addrules/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/double-coding-lab/flow2spec/f2s-kb-addrules"><img src="https://agentmods.dev/badge/skills/double-coding-lab/flow2spec/f2s-kb-addrules.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 | $0.00075 | $0.03404 |
| Opus 5.5 | $0.00030 | $0.01362 |
| Sonnet 5.5 | $0.00015 | $0.00681 |
| Haiku 4.5 | $0.00007 | $0.00340 |
Grade A, and why
f2s-kb-addRules 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.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
任务路径：凡
.task/落盘与续作，**必须以rules/f2s-task解析的TASK_ROOT为准（.task或.task/<developerId>；config → git → legacy）。下文若仍出现.task/todo.json/.task/active/，均视为TASK_ROOT/...的简写。
执行口径：本技能只维护
.Knowledge（topics/index/manifest-routing/matchers分片），不改配置根rules/skills，不动业务代码，不创建.task/（口述规则属于元配置变更，不是业务变更追踪）。
f2s-kb-addRules：用户口述规则进知识库
与既有技能的边界
- 与
f2s-kb-feat区分：f2s-kb-feat强绑「代码实现 + KB 同步」，命中changeTracking.feat会创建.task/；本技能只沉淀规则，不改代码、不追踪任务。 - 与
f2s-kb-build区分：f2s-kb-build输入是.Knowledge/stock-docs/<file>_终稿.md；本技能输入是用户当场口述的规则文本。 - 与
f2s-kb-add区分：f2s-kb-add输入是「多文件源码 / 配置」聚合到 stock-docs；本技能跳过 stock-docs，直接落 topic。
编排（主 / 子 agent）
subAgent/switchAgentVerification语义以统一入口为唯一事实源（Cursor/Claude 读rules/f2s-flow2spec-unified-entry.*；Codex 读.codex/topics/f2s-flow2spec-unified-entry.md）。本 SKILL 不复述。- 默认主 agent 全流程执行——口述规则单条短文，拆子收益低于 context 切换成本。
- 写权硬约束：
.Knowledge/manifest-routing.json/.Knowledge/index.md恒由主 agent 落盘。 - 落盘侧自验。
输入
- 一条或一段用户口述的规则文本（自由文本即可，无固定格式）。
- 用户不需要指定目标主题、文件名、
alwaysApply等参数；由本技能判定与提议。
强制前置：Read 创作侧准则
执行任何步骤前，须先 Read rules/f2s-topic-authoring.* 全文（Cursor/Claude：rules/f2s-topic-authoring.mdc；Codex：.codex/topics/f2s-topic-authoring.md），后续命名 / 骨架 / 依赖判定 / DAG 最小化 / 写盘权属均以该条为准。
步骤 1：意图归一
把用户口述文本归一为可落盘的"规则单元"：
- 抽取约束句式（"做 X 时必须 / 禁止 / 优先 Y"）或流程描述（"X 的处理顺序是 A→B→C"）；
- 标识规则适用场景（触发条件、文件路径范围、生命周期阶段等）；
- 不替用户引申、不补未说的边界——口述什么写什么，模糊处保留并在步骤 3 询问。
步骤 2：扫存量主题（必须）
- Read
.Knowledge/manifest-routing.json取topicPaths全集； - Read
.Knowledge/index.md主题表，按主题 id + 一句话意图扫一遍； - 必要时按规则正文中的关键词逐个 Read 候选
topics/<id>.md头部 10–30 行（不要全文加载所有 topic）； - 输出候选清单（重合度高 → 低，至多 3 个）作为步骤 3 的输入。
步骤 3：新建 vs 并入判定（必须，与用户确认）
向用户展示候选，按下列分支提议：
- 高重合（口述规则明显是某存量主题的细化 / 补充 / 例外）→ 提议「并入
topics/<existing>.md」，并指出拟插入位置（章节名 / 段落锚点）。 - 无重合 / 低重合（找不到合适宿主）→ 提议「新建
topics/<新 id>.md」；新 id 由本技能按规则正文生成 kebab-case，遵循f2s-topic-authoring命名约束（无版本后缀、无个人花名、与index.md既有标题不冲突）。 - 跨多个主题（一条口述同时约束 ≥2 个主题）→ 暂停，向用户呈现拆分选项：
- 选项 A：拆为 ≥2 条规则单元，分别并入对应主题；
- 选项 B：选主归并到一个主题，其它主题以一行交叉引用提示；
- 选项 C：新建一个总纲性主题统辖，旧主题加引用——仅在该规则确实横切多个领域时使用。
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 Changed 49e5a6c164f4
- 1mo ago First seen · 169 lines · 75 tokens per session scan A 37c7ce5979fb
f2s-kb-addRules is a skill published in the GitHub repository double-coding-lab/Flow2Spec (52 stars, last pushed 6d ago), licensed MIT. It adds 75 tokens to every session and 3,404 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
shellm
Reference for the shellm system — recursive LLM shell, identity management, memory, skills, trajectory, and all CLI tools. Use when working on shellm itself, debugging agent behavior, or understanding how the pieces fit together.