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/danshapiro/kilroy/agents-mdgit clone --depth 1 https://github.com/danshapiro/kilroyWhat 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 | $0.02772 | $0.02772 |
| Opus 5 | $0.01386 | $0.01386 |
| Sonnet 5 | $0.00554 | $0.00554 |
| Haiku 4.5 | $0.00277 | $0.00277 |
Grade B, and why
kilroy AGENTS.md scanned grade B with 1 finding 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 3d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
gofmt -l . | grep -v '^\./\.claude/' | grep -v '^\.claude/' How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
What Kilroy Is
Kilroy is a local-first Go CLI for running software-factory pipelines in a Git repository. There is a skill to convert English requirements into DOT graphs. Then it validates graph semantics and executes stages with checkpoint commits and a run history backed by cxdb. Foundational specs that are in docs/strongdm/attractor.
Use Kilroy in this order: build the binary, generate or write a graph, validate it, then run it with a config file. Typical flow: go build -o ./kilroy ./cmd/kilroy, ./kilroy attractor ingest -o pipeline.dot "<requirements>", ./kilroy attractor validate --graph pipeline.dot, then ./kilroy attractor run --graph pipeline.dot --config run.yaml.
What you're doing here - the Prime Directive.
If you can see this message, then you are not here to use Kilroy - YOU ARE HERE TO IMPROVE KILROY. If Kilroy fails to build a project:
- Don't fix the project
- Don't fix the dotfile
- Don't fix the system so it works for this project Use the knowledge you've gained from the failure to make the system more robust for every project. Your changes should work for every project, every language, every system. Of course, specific user instructions may override this, or any other section.
Think like a user
Think about a blank slate agent that is trying to properly create a dotfile using the dotfile skill and then run it with the attractor. What mistakes would it make? What ergonomics would steer it away? How can you make that robust for every possible project the attractor could work on, not just this one? How can you do that without asking it to know the impossible, like how hard a problem is or how long something might take?
Canonical Specs
These three specs are the true north for system design. If you are making a change that relates to one of their areas, you must consult the relevant spec first to see what the idiomatic solution is.
- Unified LLM Spec (
docs/strongdm/attractor/unified-llm-spec.md): Provider-agnostic LLM client — a singleClientinterface across LLM endpoints with unified types, retry/backoff, streaming, and tool calling. Key implementation:internal/llm/(client, types, errors, retry, generate, streaming) andinternal/llm/providers/(per-provider adapters).
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.
- 3d ago First seen · 182 lines · 2,772 tokens per session scan B 4dfb7239f066
kilroy AGENTS.md is an instructions file published in the GitHub repository danshapiro/kilroy (218 stars, last pushed 4mo ago), licensed MIT. It adds 2,772 tokens to every session, about $0.0139 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). 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).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
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.
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 oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.