agentleFS
igorkravcenkoigorkravcenko/snowshoe/AGENTS.md

snowshoe

AGENTS.md1 starsChanged 35 days agoApache-2.0View on GitHub

Entrypoint for agents working in this repo. Snowshoe (provisional) — Don't let your agents outrun your understanding. Keep your footing. A git-native personal comprehension map of a repository (Apache-2.0). Implementation status: HP1–4 CLI + tryable map UI/skill; routine ADRs A/B remain proposed. Install / PATH: snowshoe via @igorkravcenko/snowshoe; informal snow is not PATH. Skills/agents call snowshoe. Default signal is skill/human → CLI (work next gates init / routine refresh / advance). init does not install git hooks; opt-in hooks remain…

The file

We split this AGENTS.md into the rules it gives an agent

6 rules. About 0 are common, 3 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read docs/brain/START_HERE.md.

    line 5
  2. Distinctive:

    Follow the read order there: CURRENT → ROADMAP → EXPERIMENTS.

    line 6
  3. Distinctive:

    Treat CURRENT + accepted ADRs as truth.

    line 8
  4. Very specific:

    No learning/quiz/verify, agent spawn, or fake features beyond the HP1–4 CLI + tryable map UI/skill unless CURRENT + an ADR say so.

    line 18
  5. Very specific:

    Do not invent ARR, users, or competitors.

    line 20
  6. Distinctive:

    Do not import trading / Nautilus / portfolio / bots from other repos.

    line 21

≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
AGENTS.md

AGENTS

Entrypoint for agents working in this repo.

  1. Read docs/brain/START_HERE.md.
  2. Follow the read order there: CURRENT → ROADMAP → EXPERIMENTS.
  3. Load .cursor/skills/brain-protocol/SKILL.md before changing product claims or behavior.
  4. Treat CURRENT + accepted ADRs as truth. Evidence, notes, and experiments are not.

Product (one line)

Snowshoe (provisional) — Don't let your agents outrun your understanding. Keep your footing. A git-native personal comprehension map of a repository (Apache-2.0). Implementation status: HP1–4 CLI + tryable map UI/skill; routine ADRs A/B remain proposed. Install / PATH: snowshoe via @igorkravcenko/snowshoe; informal snow is not PATH. Skills/agents call snowshoe. Default signal is skill/human → CLI (work next gates init / routine refresh / advance). init does not install git hooks; opt-in hooks remain intent (CLI not shipped). Stack + clarifications: ADR-2026-09-25-implementation-stack. Slices: ADR-2026-09-26-vertical-slice-cli, ADR-2026-09-27-map-ui-and-skill, ADR-2026-09-27-skill-drain-loop.

Hard rules

  • English for docs/brain/**, skills, rules, this file, commits, and PRs.
  • User-facing chat: English by default (see .cursor/rules/agent-comms.mdc). Maintainer Russian-chat preference is private overlay only.
  • No learning/quiz/verify, agent spawn, or fake features beyond the HP1–4 CLI + tryable map UI/skill unless CURRENT + an ADR say so.
  • CI: docs brain-docs lint (ADR-2026-09-25-brain-docs-ci) plus app CI (typecheck, bun test, Biome) (ADR-2026-09-27-app-ci-biome). No lefthook / husky / pre-commit yet. Product git-hook CLI is not shipped.
  • Do not invent ARR, users, or competitors. Unknown stays unknown.
  • Do not import trading / Nautilus / portfolio / bots from other repos.
  • Quality: Chief of Staff owns consistency audit on docs PRs before merge (.github/agents/auditor.agent.md / grill-canon). Agents draft packages carefully; do not race a shared local clone.

Skills

SkillWhen
brain-protocolSession start; any canon or behavior change
grillingStress-test a plan or decision (rounds + frontier)
grill-meUser says "grill me" / wants to be interviewed
grill-canonAudit CURRENT/ADRs for staleness or contradiction
snowshoeProduct skill at skills/snowshoe/ (Cursor: .cursor/skills/snowshoe symlink). Gate: PATH snowshoe (install.md only if missing), then drain.md (work next) or learn.md. Working repo without skill files: snowshoe skill install --json --skills-path <harness-skills-dir>
snowshoe-scratchSatellite skill at skills/snowshoe-scratch/ (Cursor: .cursor/skills/snowshoe-scratch symlink). Path without the map: ~/.snowshoe/learn/<sha256(utf8(realpath))>; optional atlas is map status --json --cwd only (optional help --json). Do not drain, init, or write the ledger. Working repo: snowshoe skill install copies it with the product skill.
.github/agents/auditor.agent.mdRead-only consistency audit (CoS before merge)

Maintainer-only overlay lives in the sibling private repo snowshoe-maintainers. Link with ./scripts/link-private-overlay.sh (or set SNOWSHOE_MAINTAINERS):

  • .cursor/skills/gan-* — Orca GAN skills
  • docs/private — GTM / monetization research / competitive evidence / naming history
  • .cursor/rules/maintainer-chat.mdc — optional Russian chat preference

Symlinks are gitignored. Public CURRENT/ADRs must not depend on docs/private links. Product CLI/map does not depend on the overlay.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.