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 lyonzin/knowledge-rag --skill rag-index-decisionsgit clone --depth 1 https://github.com/lyonzin/knowledge-ragWrote 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/lyonzin/knowledge-rag/rag-index-decisions)<a href="https://agentmods.dev/skills/lyonzin/knowledge-rag/rag-index-decisions"><img src="https://agentmods.dev/badge/skills/lyonzin/knowledge-rag/rag-index-decisions/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/lyonzin/knowledge-rag/rag-index-decisions"><img src="https://agentmods.dev/badge/skills/lyonzin/knowledge-rag/rag-index-decisions.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 | $0.00072 | $0.01961 |
| Opus 5.5 | $0.00029 | $0.00784 |
| Sonnet 5.5 | $0.00014 | $0.00392 |
| Haiku 4.5 | $0.00007 | $0.00196 |
Grade A, and why
rag-index-decisions 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 19d 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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
rag-index-decisions — close the feedback loop
When to use this skill
Trigger this skill when, during a session, the team (or the agent + user together) produces:
- A design decision with tradeoffs discussed (worth an ADR)
- A novel bug fix whose root cause is non-obvious
- A convention agreed on ("from now on we do X for Y")
- A postmortem summary — even a paragraph
- A URL / doc / paper that shaped the decision (worth ingesting via
add_from_url)
Do NOT trigger for:
- Trivial fixes (typo, formatting, obvious one-liner)
- Session-only context that will not matter next time
- Highly sensitive material that should NOT be in the RAG (secrets, PII, WIP negotiations)
- Duplicates of things already indexed
What this skill commits to
When the session produces something worth remembering, the agent proactively suggests indexing it — either:
- As a new file written to
documents/and indexed viaadd_document, OR - As a URL ingestion via
add_from_urlif the reference lives elsewhere
The agent does NOT silently index things — always asks the user first, offering a preview of the content and where it will go.
Steps
-
Recognize the moment. The session hit one of the triggers above.
-
Draft the artifact in your head. Typical shapes:
- ADR (Architecture Decision Record): ~200-500 words, structured as Context / Decision / Consequences.
- Runbook update: step-by-step reproducible playbook.
- Postmortem: what happened / root cause / fix / prevention.
- Coding standard: "for X, do Y (not Z), because W."
-
Propose to the user:
"This decision looks worth remembering. I can:
(a) Create
docs/adr/0045-token-storage.mdwith a 300-word ADR summarizing what we agreed, then index it. (b) Just record the summary here, no indexing.Which?"
-
If the user picks indexing, submit the approved text.
add_documentwrites the file and indexes it. Paths are relative to the configured documents directory, so do not repeat a leadingdocuments/component:
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.
- 19d ago Changed · +4 lines 99066aed0a47
- 1mo ago First seen · 210 lines · 72 tokens per session scan A 05df017b3aee
rag-index-decisions is a skill published in the GitHub repository lyonzin/knowledge-rag (300 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 1,961 once invoked, about $0.0003 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.
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