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/openbitfun/skill_tree/skill-tree-generatornpx skills add openBitFun/skill_tree --skill skill-tree-generatorgit clone --depth 1 https://github.com/openBitFun/skill_treeWhat 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 | $0.00104 | $0.08708 |
| Opus 5 | $0.00052 | $0.04354 |
| Sonnet 5 | $0.00021 | $0.01742 |
| Haiku 4.5 | $0.00010 | $0.00871 |
Grade A, and why
skill-tree-generator 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.
How it starts
The opening of the file, as written. The whole thing — 538 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Tree Generator
Usage
/skill-tree-generator <skill-name-or-skill-path-or-description>
/skill-tree-generator --aggregate skill1,skill2,... [--domain domain-name] [--no-decompose]
/skill-tree-generator --update <tree-path> --add <skill>
| 输入特征 | Mode | 描述 |
|---|---|---|
| 单个 skill 路径/描述，无特殊 flag | Mode 1 | 将单体 skill 转为路由树 |
--aggregate skill1,skill2,... |
Mode 2 | 聚合多个 skill 为统一跨域树 |
--update <tree-path> --add <skill> |
Mode 3 | 增量更新已有 tree |
可选 flag：
| Flag | 适用 Mode | 作用 |
|---|---|---|
--domain <name> |
Mode 2 | 声明同域聚合，ROOT.md 按域内能力差异路由 |
--no-decompose |
Mode 2 | 跳过 Step A1 能力拆解，所有源 skill 一律按单叶处理。仅当源 skill 已预先拆到原子粒度时使用 |
Overview
Transform monolithic skills into modular, hierarchical skill-trees (ROOT.md → ROUTER.md → SKILL.md) with dynamic routing. Use when:
- A skill has grown too complex and needs modularization
- Multiple distinct workflows exist within a single skill
- Multiple related skills need to be unified under one routing tree
- Cross-domain workflows span multiple skills
- Overlapping capabilities across skills need deduplication
- An existing skill-tree needs new skills or capabilities added
Strict Conformance
Before creating or modifying tree output, read and follow references/strict_conformance.md. Do not use substitute workflows, fast versions, heuristic-only splitting, or partial validation. If full conformance is impractical, stop and report the blocker before continuing.
Mode 1: Single Skill Tree Generation
Generate a routing tree for a single skill.
Input: Skill path or description
Output: Complete tree structure in {skill-name}-tree/
Example:
/skill-tree-generator web-development
Mode 1 Step 1: Analyze Input Skill
First, analyze the input skill to identify:
- Core domains - What major functional areas does the skill cover?
- Sub-domains - Within each core domain, what sub-categories exist?
- Leaf capabilities - What specific tasks/endpoints are at the lowest level?
- Routing criteria - What signals distinguish one path from another?
What ships with it
9 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.
- references/cross_cutting_template.md 3.8 KB
- references/error_handling.md 11 KB
- references/leaf_template.md 6.8 KB
- references/lessons_learned.md 19 KB
- references/overview_template.md 4.5 KB
- references/root_template.md 10 KB
- references/router_template.md 8.5 KB
- references/strict_conformance.md 1.7 KB
- references/validation_template.md 21 KB
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 · 538 lines · 104 tokens per session scan A d17e3371b9a9
skill-tree-generator is a skill published in the GitHub repository openBitFun/skill_tree (64 stars, last pushed 12d ago), licensed MIT. It adds 104 tokens to every session and 8,708 once invoked, about $0.0005 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.
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📝 任务完成后归档
重要提醒: 每次完成复杂调试或开发任务后，主动执行此流程！ 将学到的经验归档为 skill，供以后参考。不要等用户提醒。.