Borrowing it
Nothing to install: this file belongs to shinpr/agentic-code. 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/shinpr/agentic-code/main/AGENTS.mdgit clone --depth 1 https://github.com/shinpr/agentic-codeWrote 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/shinpr/agentic-code/agents-md)<a href="https://agentmods.dev/instructions/shinpr/agentic-code/agents-md"><img src="https://agentmods.dev/badge/instructions/shinpr/agentic-code/agents-md/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/instructions/shinpr/agentic-code/agents-md"><img src="https://agentmods.dev/badge/instructions/shinpr/agentic-code/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00760 | $0.00760 |
| Opus 5.5 | $0.00304 | $0.00304 |
| Sonnet 5.5 | $0.00152 | $0.00152 |
| Haiku 4.5 | $0.00076 | $0.00076 |
Grade A, and why
agentic-code 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 2mo 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Goal
Use the repository's task definitions and skills to complete the requested outcome with the minimum sufficient work and observable verification.
Operating Boundaries
- Preserve confirmed requirements, explicit non-goals, repository contracts, and user authority.
- Treat reuse and no-change as valid conclusions when repository evidence shows the outcome is already satisfied.
- Require user approval when the product outcome, scope, a major durable design decision, or an irreversible external state would change.
- Consider work complete when the requested behavior is observable through the narrowest sufficient verification boundary.
Session Setup
For repository work:
- Inspect the project structure.
- Load
.agents/skills/metacognition/SKILL.mdand keep it active for the session.
Task Routing
Before loading task-analysis.md, check whether repository inspection is needed to decide how to execute the request.
- If not, execute the request directly.
- If yes, load
.agents/tasks/task-analysis.mdand use its result to select the path.
Small / Single Task
- Load the task definition that owns the requested result.
- Load only the skills required for the current decision or action.
- Execute directly without the workflow.
Medium / Large Work
- Follow
.agents/workflows/agentic-coding.mdafter the user approves the recommended path. - Medium means one coherent outcome coordinates across a responsibility boundary or requires a durable design decision.
- Large means multiple independently valuable outcomes require separate design decisions.
- File count is supporting evidence, not the scale rule.
Task Definitions and Skills
- Task definitions describe the result, required inputs, execution criteria, and completion evidence for one kind of work.
- Skills supply reusable judgment and quality rules.
- Read a task or skill at the point where its rules affect the next decision; do not preload future phases.
- When a task names required skills, confirm they are active before executing that task.
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.
- 2mo ago First seen · 93 lines · 760 tokens per session scan A 5c2c951121f7
agentic-code AGENTS.md is an instructions file published in the GitHub repository shinpr/agentic-code (50 stars, last pushed 7d ago), licensed MIT. It adds 760 tokens to every session, about $0.0030 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.
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).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.