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 instructions/ebispot/ols4/agents-mdgit clone --depth 1 https://github.com/EBISPOT/ols4What 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 | $0.00245 | $0.00245 |
| Opus 5 | $0.00122 | $0.00122 |
| Sonnet 5 | $0.00049 | $0.00049 |
| Haiku 4.5 | $0.00024 | $0.00024 |
Grade A, and why
ols4 AGENTS.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 2d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- copilot AGENTS.md — 100% identical, 0 lines differ
- qwykz AGENTS.md — 100% identical, 0 lines differ
- dml-bps-mcp AGENTS.md — 88% identical, 2 lines differ
What it actually says
graphify
This project has a knowledge graph at graphify-out/ with god nodes, community structure, and cross-file relationships.
When the user types /graphify, use the installed graphify skill or instructions before doing anything else.
Rules:
- For codebase questions, first run
graphify query "<question>"when graphify-out/graph.json exists. Usegraphify path "<A>" "<B>"for relationships andgraphify explain "<concept>"for focused concepts. These return a scoped subgraph, usually much smaller than GRAPH_REPORT.md or raw grep output. - Dirty graphify-out/ files are expected after hooks or incremental updates; dirty graph files are not a reason to skip graphify. Only skip graphify if the task is about stale or incorrect graph output, or the user explicitly says not to use it.
- If graphify-out/wiki/index.md exists, use it for broad navigation instead of raw source browsing.
- Read graphify-out/GRAPH_REPORT.md only for broad architecture review or when query/path/explain do not surface enough context.
- After modifying code, run
graphify update .to keep the graph current (AST-only, no API cost).
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.
- 2d ago First seen · 13 lines · 245 tokens per session scan A 6a4a2e13159f
ols4 AGENTS.md is an instructions file published in the GitHub repository EBISPOT/ols4 (101 stars, last pushed 4d ago), licensed Apache-2.0. It adds 245 tokens to every session, about $0.0012 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 2026-08-30.
Other instructions, from other repositories
brainapi2 AGENTS.md
AGENTS.md instructions for Lumen-Labs/brainapi2: Project agent guidance for benchmarks: see benchmarks/AGENTS.md.
brainapi2 CLAUDE.md
Claude Code instructions for Lumen-Labs/brainapi2, a project described as: BrainAPI is a knowledge graph–powered AI memory layer that transforms unstructured data into structured knowledge, enabling intelligent search, recommendations, and contextual memory for AI agents and applications.
obsidian-llm-wiki AGENTS.md
Instructions for green-dalii/obsidian-llm-wiki, covering llm wiki plugin project development standards, 🛡️ six-gate quality closure, gate 1: five-gate automated, gate 2: no side effects and gate 3: no breaking changes.
obsidian-llm-wiki CLAUDE.md
Instructions for green-dalii/obsidian-llm-wiki, a project described as: Karpathy's LLM Wiki implementation plugin for Obsidian - turns notes and PDFs into a linked, LLM-powered knowledge base with entity pages, concept pages, graph-powered Q&A, and local-first privacy.
raytsystem-public-os CLAUDE.md
Instructions for romarayt/raytsystem-public-os, covering compatibility pointer and documentation synchronization.
raytsystem-public-os AGENTS.md
Instructions for romarayt/raytsystem-public-os, covering raytsystem — agent routing, invariants, commands, skill routing and documentation.