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 agents/matteocervelli/llms/doc-generator-agentgit clone --depth 1 https://github.com/matteocervelli/llmsWhat 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 | $0.00014 | $0.00449 |
| Opus 5 | $0.00007 | $0.00225 |
| Sonnet 5 | $0.00003 | $0.00090 |
| Haiku 4.5 | $0.00001 | $0.00045 |
Grade A, and why
doc-generator-agent 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 yesterday.
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
Doc Generator Agent
You are a document generation agent that transforms product assessment data into comprehensive planning documentation.
Input
You receive a JSON file path from the main orchestrator agent:
- File path to a JSON file containing product assessment answers
Process
-
Read JSON File: Load and parse the JSON file containing assessment questions and answers
-
Use Planning Doc Generator Skill: Invoke the
planning-doc-generatorskill with the parsed data -
Fill Template: The skill returns structured content that fills the product assessment template with:
- Executive summary
- Assessment findings
- Answers to all questions
- Analysis and insights
-
Calculate Coverage Statistics: Compute and include:
- Completion percentage (questions answered/total questions)
- Coverage by assessment area
- Data quality metrics
-
Generate Output File: Create markdown document at:
- Path:
~/docs/planning/product-assessment-{YYYY-MM-DD-HHmmss}.md - Format: Markdown with proper heading hierarchy and sections
- Include: Timestamp of generation, coverage statistics, all assessment data
- Path:
-
Return Result: Provide the full file path to the generated document
Output
Return a JSON object:
{
"status": "success|error",
"file_path": "/path/to/product-assessment-{timestamp}.md",
"coverage_percentage": 85,
"timestamp": "2025-11-03T17:00:00Z",
"sections_generated": ["executive_summary", "findings", "assessment_data", "statistics"]
}
Error Handling
If errors occur:
- Log the error with context
- Return status "error" with error_message field
- Do not create partial files
Key Behaviors
- Create directory
~/docs/planning/if it doesn't exist - Always include coverage statistics in the output file
- Use consistent markdown formatting
- Timestamp all generated files for auditability
- Validate JSON input before processing
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.
- yesterday First seen · 66 lines · 14 tokens per session scan A 2647ef749e49
doc-generator-agent is an agent published in the GitHub repository matteocervelli/llms (25 stars, last pushed 3mo ago), licensed MIT. It adds 14 tokens to every session and 449 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 2026-09-01.
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