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/davidvujic/my-eca-config/agents-mdgit clone --depth 1 https://github.com/DavidVujic/my-eca-configWrote 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/davidvujic/my-eca-config/agents-md)<a href="https://agentmods.dev/instructions/davidvujic/my-eca-config/agents-md"><img src="https://agentmods.dev/badge/instructions/davidvujic/my-eca-config/agents-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 | $0.01719 | $0.01719 |
| Opus 5 | $0.00860 | $0.00860 |
| Sonnet 5 | $0.00344 | $0.00344 |
| Haiku 4.5 | $0.00172 | $0.00172 |
Grade A, and why
my-eca-config 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 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Default Skills
All agents must load the following skill by default:
skills/concise-style/SKILL.md
Review instructions
When the user asks for a code review / PR review / diff review, use the code-review subagent configured in agents/code-review.md.
Five Whys instructions
When the user asks for a 5 Whys analysis, use the five-whys subagent configured in agents/five-whys.md.
Changes summary instructions
When the user asks for a changes summary, use the changes-summary subagent configured in agents/changes-summary.md.
Pull Request instructions
When the user asks to make a pull request, use the pull-request subagent configured in agents/pull-request.md.
Planning instructions
When the user asks to plan an implementation or requests a step-by-step plan before coding, load the planning-style skill configured in skills/planning-style/SKILL.md via eca__skill before writing the plan.
Commit instructions
When the user asks to create a commit or uses the /commit command, use the commit subagent configured in agents/commit.md.
Implementation instructions
When the user asks to implement a plan, write code, refactor, or apply changes, use the implement subagent configured in agents/implement.md.
QA check instructions
When the user asks to check the changes of code, use the qa-check subagent configured in agents/qa-check.md to run linting and unit tests before considering the work complete.
CodeScene instructions
Treat Code Health as the source of truth for maintainability. Aim for Code Health 10.0 on AI-touched code; 9+ is not "good enough." When Code Health regresses or violates goals, refactor — do not declare done. When in doubt, call a CodeScene MCP tool instead of guessing.
Safeguard AI-generated code (mandatory before commit / PR)
Before recommending a commit or opening a PR on AI-touched code, load the safeguarding-ai-generated-code skill via eca__skill and follow it. It gates changes with pre_commit_code_health_safeguard (staged files) and analyze_change_set (branch vs base ref), and falls back to code_health_review on any regression.
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 · 92 lines · 1,719 tokens per session scan A 4db8f2ce9b53
my-eca-config AGENTS.md is an instructions file published in the GitHub repository DavidVujic/my-eca-config (11 stars, last pushed 8d ago), licensed MIT. It adds 1,719 tokens to every session, about $0.0086 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
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
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spec-kit AGENTS.md
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langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.