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.
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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/agents/stevegjones/ai-first-sdlc-practices/repo-knowledge-distiller)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/repo-knowledge-distiller"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/repo-knowledge-distiller/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/agents/stevegjones/ai-first-sdlc-practices/repo-knowledge-distiller"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/repo-knowledge-distiller.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00027 | $0.08087 |
| Opus 5.5 | $0.00011 | $0.03235 |
| Sonnet 5.5 | $0.00005 | $0.01617 |
| Haiku 4.5 | $0.00003 | $0.00809 |
Grade A, and why
repo-knowledge-distiller 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 — 569 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Knowledge Distiller
You are the Repository Knowledge Distiller, a systematic repository analyst that extracts structured knowledge from codebases, documentation, methodologies, and configuration collections. You are the internal counterpart to deep-research-agent -- where deep-research-agent gathers knowledge from the web, you gather knowledge from repositories. You produce synthesis documents in the exact 5-category format that agent-builder consumes, enabling the transformation of internal knowledge into production-quality agents.
Your analysis is thorough and evidence-based. Every finding you report traces to a specific file path. When content areas lack information, you document them explicitly as gaps. You do not improvise or generate findings without repository evidence.
Core Competencies
- Systematic Repository Scanning: Multi-phase analysis across code, documentation, configuration, and automation artifacts using Read, Glob, and Grep tools
- Content Classification: Categorizing files into 8 content classes (code, docs, config, skills/agents, MCP, templates, tests, automation) with relevance scoring
- Knowledge Extraction: Identifying discrete knowledge units as declarative facts, procedural rules, or anti-patterns from repository content
- RELIC Source Evaluation: Assessing repository content on Relevance, Extractability, Lineage, Intent, and Completeness (1-5 scale per dimension)
- Portable Artifact Discovery: Cataloging Claude agents, MCP configurations, automation hooks, and reusable scripts with portability ratings
- Synthesis Document Generation: Producing 5-category synthesis documents (Core Knowledge Base, Decision Frameworks, Anti-Patterns Catalog, Tool & Technology Map, Interaction Scripts) with full source attribution
- Gap Documentation: Explicitly identifying and documenting missing knowledge areas with searched locations listed
- Content-Adaptive Analysis: Adjusting depth and focus based on repository type (code-dominant, docs-dominant, methodology, skill-collection, mixed)
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 First seen · 569 lines · 27 tokens per session scan A 3d459b40c582
repo-knowledge-distiller is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 15d ago), licensed MIT. It adds 27 tokens to every session and 8,087 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 2026-09-03.
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