Awesome-omni-skill repo-a-policy-selftest-gate
Enforce Repo A DDC policy and acceptance gates before PRs. Use when changing policy files, node runtime behavior, guardrail-sensitive config, or validation tooling that must satisfy AGENTS.md acceptance commands.
install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data-ai/repo-a-policy-selftest-gate" ~/.claude/skills/diegosouzapw-awesome-omni-skill-repo-a-policy-selftest-gate && rm -rf "$T"
manifest:
skills/data-ai/repo-a-policy-selftest-gate/SKILL.mdsource content
Repo A DDC Policy and Selftest Gate
Use this skill to run required pre-PR validation in
<PRIVATE_REPO_A>.
Workflow
- Review
,AGENTS.md
, and policy manifests before coding.INSTRUCTIONS.md - Run lint/type gates.
- Run mesh-ready selftest against
.config/device_policy.json - Run focused tests for changed modules.
- Ensure policy/config changes remain documented and intentional.
Scope Boundary
Use this skill for
<PRIVATE_REPO_A> policy/selftest acceptance gates only.
Do not use this skill for:
policy/schema or trace/ranking contracts.<PRIVATE_REPO_C>- General boundary-governance checks in other repos.
- Runtime bridge or hardware troubleshooting lanes.
Required Commands
Run from
<PRIVATE_REPO_A> root:
ruff check . mypy repo_a_node python -m repo_a_node --policy config/device_policy.json --selftest config/mesh_ready_selftest.yaml pytest -q
Policy Safety Notes
- Never hardcode secrets, URLs, or policy overrides.
- Do not relax canary/redundancy defaults without docs and policy updates.
- Keep governance boundaries aligned with
.BOUNDARIES.md
Reference
references/gate-checklist.md
Loopback
If this lane is unresolved, blocked, or ambiguous:
- Capture current evidence and failure context.
- Route back through
for chain recalculation.$skill-hub - Resume only after the updated chain returns a deterministic next step.