crawfish-authoring-policies-skills

name	crawfish-authoring-policies-skills
description	Author policies/*.py (module-level Policy instances — consequential static config) and skills/*.md (bundled skills). Load when adding a guardrail/routing/permission policy or a bundled skill. A policy is static-only.
user-invocable	false
allowed-tools	Read, Grep

Authoring policies/*.py & skills/*.md

Derived from docs/specs/craw-code/authoring/policies-skills.md. Golden: demo/craw-code-golden/policies/spend_guard.py + skills/*.md.

policies/*.py — module-level Policy instances

Each policies/*.py declares one or more module-level Policy instances. The compiler discovers them into DefinitionAssets.policies; an agent binds one by name in front-matter policies: [...]. Binding an unknown policy fails at load with DefinitionLoadError.

"""spend_guard — a guardrail Policy: a per-batch model-spend cap."""
from __future__ import annotations
from crawfish.core import Policy, PolicyKind

spend_guard = Policy(
    name="spend_guard",
    kind=PolicyKind.GUARDRAIL,
    rules={"max_usd_per_batch": 5.0},
)

A Policy is constructed with name, a kind (PolicyKind.GUARDRAIL / ROUTING / PERMISSION), and a rules dict. (Policy has no description field — it is name + kind + rules.)

A policy is consequential, therefore static-only

A Policy is consequential, static config — what an agent may or may not do, spend caps, which sources/sinks it may touch. It is never derived from a fluid or model-derived value. with_policy adds a static policy and folds it into the content sha.

Spine rule (consequential-static-only): Consequential sink targets, idempotency keys, and consequential outputs are static-only.

skills/*.md — bundled skills

Each skills/*.md is a bundled skill the Definition carries; the compiler discovers them by filename into DefinitionAssets.skills. A skill is a markdown body (optionally with front-matter) — reusable instructions, not a consequential slot.