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/shinpr/agentic-code/agents-mdgit clone --depth 1 https://github.com/shinpr/agentic-codeWhat 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 | $0.00760 | $0.00760 |
| Opus 5 | $0.00380 | $0.00380 |
| Sonnet 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 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.
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.
- 2d 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 (49 stars, last pushed 3d ago), licensed MIT. It adds 760 tokens to every session, about $0.0038 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
codedb AGENTS.md
Instructions for justrach/codedb, covering codedb agent guidelines, what codedb is (and isn't), review guidelines, pre-merge verification and security-sensitive areas.
agent-rules testing.instructions.md
Instructions for lirantal/agent-rules, covering testing guidelines for node.js applications, general testing principles, guiding principles, descriptive test naming (three-part structure) and structure tests by the aaa pattern.
turbo-flow CLAUDE.md
Claude Code instructions for marcuspat/turbo-flow, covering claude.md — turbo flow, what this repo is, key files and conventions.
agent-rules child-process.instructions.md
Instructions for lirantal/agent-rules, covering system processes secure coding guidelines, your mission and spawning system processes.
free-ai-gateway AGENTS.md
Instructions for zaber-dev/free-ai-gateway, covering 🤖 free-ai gateway - agentic development guidelines, 🏛️ monorepo architecture & package boundaries, 🛑 strict architectural rules for agents, 💻 essential developer commands and build all packages across monorepo.
bdb-dev-optimized-agent-skills CLAUDE.md
Instructions for hybridlabor-api/bdb-dev-optimized-agent-skills, covering bdb agent skills — global instructions, docs & pipeline, how many agents, safety gate — mechanically enforced, not advisory and non-negotiable.