| 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.
