shield_lock
JinDaGe
← Back to skills
extension
Category: Productivity & OfficeNo API key required

run-policy-router

Interpret the user's high-level research intent into `RUN_POLICY.yaml` and `state/POLICY_DECISION.json`.

personAuthor: TashanworldhubOpenAPI
open_in_newRepositorydownloadDownload package

run-policy-router

Goal:

  • Interpret the user's high-level research intent into RUN_POLICY.yaml and state/POLICY_DECISION.json.

Inputs:

  • one run directory root
  • run-local input.md
  • optional RUN_POLICY.yaml
  • research brief and operator constraints

Outputs:

  • updated RUN_POLICY.yaml
  • updated state/POLICY_DECISION.json

Context Loading:

  • Open skills/shared-references/schema-index.md.
  • Read packages/agent_contracts/policy.py and confirm the exact RunPolicyContract plus PolicyDecisionContract shapes before writing RUN_POLICY.yaml or state/POLICY_DECISION.json.
  • Read input.md plus any operator constraints that should influence the high-level routing axes.

Execution Contract:

  • The router must stay at the high-level policy layer and must not invent raw numeric mechanics values directly.
  • Allowed routing axes are documented in ../shared-references/policy-contract.md.
  • Downstream numeric settings are resolved separately into state/RESOLVED_RUN_CONFIG.json.
  • This skill owns canonical policy artifact emission only:
    • RUN_POLICY.yaml
    • state/POLICY_DECISION.json
  • This skill does not own numeric mechanics resolution, direct strategy routing, or downstream evolution-state writes.

Execution Steps:

  1. Open skills/shared-references/schema-index.md, then read packages/agent_contracts/policy.py before writing RUN_POLICY.yaml or state/POLICY_DECISION.json.
  2. Interpret the research brief into the allowed policy axes only.
  3. Write canonical RUN_POLICY.yaml and state/POLICY_DECISION.json.
  4. Do not invent raw numeric mechanics values that belong in state/RESOLVED_RUN_CONFIG.json.
  5. Validate the emitted policy artifacts.

Completion Rule:

  • This skill is complete only when RUN_POLICY.yaml and state/POLICY_DECISION.json have been written in canonical form and remain consistent with the selected high-level policy axes.