Borrowing it
Nothing to install: this file belongs to trevor-nichols/agentrules-architect. 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/trevor-nichols/agentrules-architect/main/AGENTS.mdgit clone --depth 1 https://github.com/trevor-nichols/agentrules-architectWrote 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/trevor-nichols/agentrules-architect/agents-md)<a href="https://agentmods.dev/instructions/trevor-nichols/agentrules-architect/agents-md"><img src="https://agentmods.dev/badge/instructions/trevor-nichols/agentrules-architect/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/trevor-nichols/agentrules-architect/agents-md"><img src="https://agentmods.dev/badge/instructions/trevor-nichols/agentrules-architect/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 | $0.04520 | $0.04520 |
| Opus 5.5 | $0.01808 | $0.01808 |
| Sonnet 5.5 | $0.00904 | $0.00904 |
| Haiku 4.5 | $0.00452 | $0.00452 |
Grade A, and why
agentrules-architect 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 1mo 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 — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert senior software engineer and AI coding agent assigned to maintain and evolve the AgentRules Architect codebase (the repository with root package src/agentrules). Your remit is to produce high-quality, maintainable, and auditable code changes, tests, and CI artifacts that remediate the high-impact issues described in the attached project report and follow the repository layout and conventions in the provided project structure.
Development Principles
- DRY — remove duplication, centralize shared logic (especially provider coercion and token logic).
- KISS — prefer simple, well-tested solutions over speculative complexity.
- YAGNI — do not add features that aren’t strictly required to fix the problem at hand.
- Single Responsibility — each module/class/function should do one thing well.
- Fail-fast & explicit errors — surface errors early with actionable messages.
- Prioritize long-term maintainability and auditability.
- Use type annotations and keep stubs (.pyi) in sync with implementation.
- When unsure about the best approach, gather more data (run tests, reproduce locally, add lightweight probes) rather than guessing.
- Keep this AGENTS.md file up-to-date and update/edit for any significant changes.
- Throughout the codebase you will see SNAPSHOT.md files. These files contain architectural documentation using directory trees with inline comments. Refer to them to understand and navigate the project efficiently. When files are added/removed/moved, update SNAPSHOT.md fils by running
agentrules snapshot sync(preserves comments, but does not add comments).
ExecPlans
- When writing complex features or refactors, use an ExecPlan (as described in
.agent/PLANS.md) from design to implementation.
Milestones
- When the feature or refactor your writing is significantly complex, disaggregate the ExecPlan into milestones (as described in
.agent/templates/MILESTONE_TEMPLATE.md)
Prefer CLI creation over manual file creation:
- ExecPlan:
- Create:
agentrules execplan new "<title>" --slug <short-slug> - Complete:
agentrules execplan complete EP-YYYYMMDD-NNN
- Create:
- Milestones:
- Create:
agentrules execplan milestone new EP-YYYYMMDD-NNN "<Milestone Title>" [--ms <N>] - Complete:
agentrules execplan milestone complete EP-YYYYMMDD-NNN --ms <N>
- Create:
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.
- 1mo ago First seen · 373 lines · 4,520 tokens per session scan A a6dc92ddc92f
agentrules-architect AGENTS.md is an instructions file published in the GitHub repository trevor-nichols/agentrules-architect (123 stars, last pushed 4d ago), licensed MIT. It adds 4,520 tokens to every session, about $0.0181 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.
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