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 skills add dandye/ai-runbooks --skill generate-taxonomygit clone --depth 1 https://github.com/dandye/ai-runbooksWrote 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/dandye/ai-runbooks/generate-taxonomy)<a href="https://agentmods.dev/skills/dandye/ai-runbooks/generate-taxonomy"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/generate-taxonomy/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/dandye/ai-runbooks/generate-taxonomy"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/generate-taxonomy.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 | $0.00018 | $0.00504 |
| Opus 5 | $0.00009 | $0.00252 |
| Sonnet 5 | $0.00004 | $0.00101 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
generate-taxonomy 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 12d 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
Generate Taxonomy Skill
Develop a hierarchical classification system or taxonomy for a knowledge base or content repository. This skill creates parent-child categorical structures to organize content effectively.
Inputs
PATH- The content source to analyze (e.g., "/knowledge-base")FACETED- (Optional) Boolean, whether to create a faceted classification (multiple dimensions) (default: false)BUSINESS_ALIGNMENT- (Optional) Boolean, whether to align with specific business goals/terminology (default: true)USER_TESTING- (Optional) Boolean, whether to include user validation methodologies in the output (default: false)
Workflow
Step 1: Content Analysis & Term Extraction
Analyze the content at PATH to identify key topics, subjects, and categories.
- Cluster documents by similarity.
- Extract common tags and keywords.
Step 2: Structure Design
Organize the extracted concepts into a hierarchy.
- Hierarchical: Define Broader Terms (Parent) and Narrower Terms (Child).
- Faceted (if enabled): Define dimensions (e.g., Topic, Format, Audience, Region).
Step 3: Business & User Alignment
- Align terms with business vocabulary (if
BUSINESS_ALIGNMENTis true). - If
USER_TESTINGis true, generate a plan for card sorting or tree testing to validate the structure.
Step 4: Taxonomy Definition
Output the defined taxonomy.
Required Outputs
A TAXONOMY_DEFINITION document (e.g., in markdown or YAML format) containing:
- Taxonomy Tree: Visual or indented list of categories.
- Facets (if requested): Definitions of classification dimensions.
- Rules: Guidelines for applying the taxonomy.
- Testing Plan (if requested): Methodologies for validation.
Quick Reference
- Purpose: Systematically classify content for retrieval optimization.
- Types: Hierarchical (Tree) vs. Faceted (Matrix).
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.
- 12d ago First seen · 59 lines · 18 tokens per session scan A 9ce619d0c898
generate-taxonomy is a skill published in the GitHub repository dandye/ai-runbooks (124 stars, last pushed 27d ago), licensed Apache-2.0. It adds 18 tokens to every session and 504 once invoked, about $0.0001 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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