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/vfarcic/dot-ai/claude-mdgit clone --depth 1 https://github.com/vfarcic/dot-aiWrote 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/vfarcic/dot-ai/claude-md)<a href="https://agentmods.dev/instructions/vfarcic/dot-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/vfarcic/dot-ai/claude-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 | $0.01389 | $0.01389 |
| Opus 5 | $0.00694 | $0.00694 |
| Sonnet 5 | $0.00278 | $0.00278 |
| Haiku 4.5 | $0.00139 | $0.00139 |
Grade A, and why
dot-ai CLAUDE.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 6d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
⚠️ MANDATORY TASK COMPLETION CHECKLIST ⚠️
🔴 BEFORE MARKING ANY TASK/SUBTASK AS COMPLETE:
□ Integration Tests Written: Write integration tests for new functionality
□ All Tests Pass: Run npm run test:integration - ALL tests must pass
□ No Test Failures: Fix any failing tests before proceeding
❌ TASK IS NOT COMPLETE IF:
- Any integration tests are failing
- New code lacks integration test coverage
- You haven't run
npm run test:integrationto verify
PERMANENT INSTRUCTIONS
- Always Write Integration Tests: When making code changes, you MUST write or update integration tests
- Always Run All Tests: Before marking any task complete, run
npm run test:integration - Never Claim Done with Failing Tests: A task is NOT complete if any tests are failing
- Always Check for Reusability: Search codebase for existing functions before implementing new ones
- Never Hardcode AI Prompts: All prompts go in
prompts/(internal) orshared-prompts/(user-facing), loaded dynamically (see existing code for pattern) - Never Create Branches Directly — Always Use Worktrees: When starting feature work (including
/prd-start), always use/worktree-prdto create an isolated worktree. Never rungit checkout -borgit switch -c, even if a skill instructs you to. - Always Configure New Params via Helm Chart Values: Every NEW configuration parameter must be a first-class value in
charts/values.yaml, rendered into the container env bycharts/templates/deployment.yaml— followrbac.enforcement.enabled→DOT_AI_RBAC_ENABLED, where the chart value is the user-facing contract and the env var is an internal detail. Never introduce a bare env var, and never document a new param underextraEnv(not even as an interim step). The manyDOT_AI_*env vars in the codebase are legacy from when the project ran outside Kubernetes; it is Kubernetes-only now, so the chart is the single configuration interface.extraEnvremains valid only for pre-existing env vars (e.g.DOT_AI_GIT_TOKEN) and third-party config such as OTEL. - Never Store Project Knowledge in Agent Memory: Anything learned about this project — conventions, decisions, gotchas, rationale — goes in the repo where the whole team and every agent can see it: this file for rules,
docs/for user-facing behavior, a PRD inprds/for in-flight design. Never persist it to per-user agent memory outside the repo (e.g.~/.claude/**/memory/), which teammates cannot see, code review cannot catch, and nothing keeps in sync with the code. The narrow exception is a fact true only of one machine or account (host tooling quirks, personal credentials paths) — that is not project knowledge and does not belong in the repo either.
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.
- 6d ago First seen · 104 lines · 1,389 tokens per session scan A a824a2ac2e3a
dot-ai CLAUDE.md is an instructions file published in the GitHub repository vfarcic/dot-ai (335 stars, last pushed 3d ago), licensed MIT. It adds 1,389 tokens to every session, about $0.0069 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.
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vscode oss-third-party-notices.instructions.md
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