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 cluster-documentsgit 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/cluster-documents)<a href="https://agentmods.dev/skills/dandye/ai-runbooks/cluster-documents"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/cluster-documents/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/cluster-documents"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/cluster-documents.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 | $0.00024 | $0.00452 |
| Opus 5.5 | $0.00010 | $0.00181 |
| Sonnet 5.5 | $0.00005 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
cluster-documents 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 2mo 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
Document Clustering Skill
Analyze a repository of documents to group them based on content similarity, topic, or purpose. This skill helps organize large collections, identify redundancies, and discover relationships.
Inputs
PATH- The repository to analyze (e.g., "/repository")SIMILARITY_THRESHOLD- (Optional) Float (0.0-1.0), threshold for grouping (default: 0.8)VISUALIZATION- (Optional) Boolean, whether to generate a visual representation (default: false)
Workflow
Step 1: Text Processing
Ingest documents from PATH.
- Normalize text (remove stop words, stemming/lemmatization).
- Generate embeddings or TF-IDF vectors for each document.
Step 2: Clustering Analysis
Apply clustering algorithms (e.g., K-Means, DBSCAN) to the document vectors.
- Group documents that meet the
SIMILARITY_THRESHOLD. - Identify outliers or unique documents.
Step 3: Cluster Labeling
Analyze the centroid or representative terms of each cluster to assign a meaningful label (Topic).
Step 4: Output Generation
Generate the clustering report.
- If
VISUALIZATIONis true, create a scatter plot or dendrogram data.
Required Outputs
A CLUSTERING_REPORT object containing:
- Cluster List: ID, Label, and List of Documents in each cluster.
- Redundancy Report: Sets of highly similar documents (potential duplicates).
- Visualization Data: (If requested) Coordinates for plotting.
Quick Reference
- Purpose: Organize unstructured content and find duplicates.
- Techniques: Text Mining, NLP, Vector Space Models.
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.
- 2mo ago First seen · 57 lines · 24 tokens per session scan A 174dec526634
cluster-documents is a skill published in the GitHub repository dandye/ai-runbooks (132 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 452 once invoked, about $0.0001 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.
cluster-documents compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| cluster-documentsdandye/ai-runbooks | Skill | 132 | 2mo ago | Apache-2.0 | A | 24 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 315k | 5d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |