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/lftpadilla/agent-dev-kit/agents-mdgit clone --depth 1 https://github.com/LFTPadilla/agent-dev-kitWhat 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 | $0.01411 | $0.01411 |
| Opus 5 | $0.00705 | $0.00705 |
| Sonnet 5 | $0.00282 | $0.00282 |
| Haiku 4.5 | $0.00141 | $0.00141 |
Grade A, and why
agent-dev-kit 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 yesterday.
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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — how agents use this repo
Instructions for coding agents working in or with agent-dev-kit. Humans read the README; agents follow this file.
What this repo is
A public, generalist kit for directing coding agents. It ships curated skills,
an adversarial /pr-review command, evals, overnight protocol templates, and
orchestration profiles. The kit composes with optional
private org skills overlays that live outside this git tree.
Layers (do not collapse them)
| Layer | Governs | Where |
|---|---|---|
| caveman | how the agent talks | external plugin |
| ponytail | what the agent builds | external plugin |
| GSD | how work flows (plan → execute → verify) | external (get-shit-done-cc for Hermes; optional pi-gsd helper) |
| superpowers (guardrails) | how code tasks are executed (TDD, root-cause debug, verification evidence) | external (obra/superpowers) |
| dev-skills | discrete capabilities | plugins/dev-skills/AGENTS.md |
| ship / overnight / orchestration | gates, isolation, long runs, and orchestration | overnight-task-kit/AGENTS.md + Agent Tutor Orchestrator |
Full map: docs/how-it-fits-together.md.
External installs: docs/external-deps.md.
Toolchain preferences
- Prefer GSD for multi-step work (plan → execute → verify).
- Prefer treehouse (or equivalent) for isolated parallel agent worktrees.
- Prefer no-mistakes as a ship gate alongside
/pr-review. - Prefer gnhf as the overnight runner; treat
overnight-task-kit/as protocol and templates, not a second ralph-loop. - Prefer AXI principles for agent contracts; prefer TOON for agent-facing structured output when the consumer is another agent or a token-sensitive channel. Use JSON when the consumer is a strict JSON API, a human-facing config file, or an existing schema that already requires JSON.
- Install extra skills via vercel-labs/skills (
npx skills); reference lifecycle packs from addyosmani/agent-skills without vendoring them here. - Prefer Tech Lead (
$tech-lead) as the unified orchestrator and mentor for multi-agent workflows, GSD execution, and learning projects. Operates acrosslearning(pedagogical tutor),flow(balanced), andautonomous(pure orchestration) modes. - Prefer Agent-Native Repository Architecture (ANRS-1.0): Use lightweight
Hub-and-Spoke
AGENTS.md, declarativeREGISTRY.yaml, and progressive disclosure. Seedocs/agent-native-architecture.mdandREGISTRY.yaml. - Prefer Superpowers execution guardrails (
test-driven-development,systematic-debugging,verification-before-completion,receiving-code-review) during task implementation while keeping GSD authoritative for project lifecycle and state.
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.
- yesterday First seen · 97 lines · 1,411 tokens per session scan A 3a4482108b3c
agent-dev-kit AGENTS.md is an instructions file published in the GitHub repository LFTPadilla/agent-dev-kit (2 stars, last pushed 4d ago), licensed MIT. It adds 1,411 tokens to every session, about $0.0071 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 2026-08-31.
Other instructions, from other repositories
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.
buildNext
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
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, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit 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.
langchain 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.