Borrowing it
Nothing to install: this file belongs to peterbeck111/knowledgelib-io. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/peterbeck111/knowledgelib-io/main/GEMINI.mdgit clone --depth 1 https://github.com/peterbeck111/knowledgelib-ioWrote 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/instructions/peterbeck111/knowledgelib-io/gemini-md)<a href="https://agentmods.dev/instructions/peterbeck111/knowledgelib-io/gemini-md"><img src="https://agentmods.dev/badge/instructions/peterbeck111/knowledgelib-io/gemini-md.svg" alt="Measured on agentmods" 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 | $0.04716 | $0.04716 |
| Opus 5 | $0.02358 | $0.02358 |
| Sonnet 5 | $0.00943 | $0.00943 |
| Haiku 4.5 | $0.00472 | $0.00472 |
Grade A, and why
knowledgelib-io GEMINI.md 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 8d 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 — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
knowledgelib.io — Claude Code Instructions
What This Is
AI Knowledge Library — structured, cited knowledge units (markdown + YAML frontmatter) optimized for AI agent consumption. Pre-verified answers that save tokens, reduce hallucinations, and cite every source.
Core value: Token arbitrage — $0.02/query vs $0.50–$5.00 in agent compute.
Daily Workflow
Follow this three-step pipeline every session:
Step 1: Check the Pipeline
Read knowledge_pipeline/tracker.md and count pending cards.
- If pending cards exist → go to Step 2.
- If no pending cards → run
/discover-topicsto find 50 new topics, then go to Step 2.
Step 2: Create Cards
Use the skills based on how many cards to produce:
| Goal | Command | What happens |
|---|---|---|
| One card | /create-card |
Picks next pending topic, researches, creates .md + .html, inserts into DB, updates tracker |
| Specific topic | /create-card --topic N |
Processes row N from tracker |
| N cards in parallel | /create-card --count N |
Spawns N subagents, each processes one topic in parallel mode |
| All pending | /create-card --batch |
Processes every pending topic sequentially |
Each card creation:
- WebSearch + WebFetch 5–8 authoritative sources (RTINGS, Wirecutter, Tom's Guide, What Hi-Fi, PCMag, Reddit)
- Creates
prototype/{category}/{subcategory}/{topic}/{version}.mdfrom template - Creates matching
.htmlwith viewport, OG, Twitter Card, all 11ai:*meta tags, Schema.org Dataset (withcreator) + BreadcrumbList JSON-LD. The HTML body must contain every section and all content from the.mdfile — see Content Parity rule below. - Runs
node db/insert_card.jsto insert into Supabase (knowledge_cards + affiliate_links) - Marks tracker row as
done
Step 3: Reconcile, Deploy, Publish
After card creation is complete, run:
npm run publish
This executes three steps in sequence:
npm run reconcile— regeneratescatalog.json+sitemap.xml(with dynamic priority from pop_index) +index.htmlknowledge units section +.well-known/ai-knowledge.json+ imports popular agent suggestions (>= 3 occurrences) to tracker.md + tracker stats from DBnpm run deploy— pushesprototype/to Cloudflare Pages (includes Functions: API + MCP). Always deploy to--project-name=knowledgelib-io.npm run indexnow:new— submits only new URLs to IndexNow (Bing, Google, Yandex)
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.
- 8d ago First seen · 263 lines · 4,716 tokens per session scan A ddb6614c2309
knowledgelib-io GEMINI.md is an instructions file published in the GitHub repository peterbeck111/knowledgelib-io (1 stars, last pushed 2mo ago), licensed MIT. It adds 4,716 tokens to every session, about $0.0236 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 2026-08-31.
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