delivery-readiness-audit
SolidSpot-check AC internal consistency and scan for pending revisions on delivery-ready stories. Activated by `/gaai-status --audit` as Section 5. Complements the standard status checks with depth checks that standard status skips for speed.
Install
Quality Score: 83/100
Skill Content
Details
- Author
- Fr-e-d
- Repository
- Fr-e-d/GAAI-framework
- Created
- 6 months ago
- Last Updated
- today
- Language
- Shell
- License
- NOASSERTION
Similar Skills
Semantically similar based on skill content — not just same category
readiness-audit
Audit a surface against a checklist to answer 'is it clean/legal/consistent to ship for THIS event?' — the recurring sibling of /foundational-review. Parallel exploration per surface, controller re-verification of every load-bearing claim, then tiered evidence-celled findings and a phased remediation plan (findings triage to phases, NOT a shipping list). Read-only probes only. No irreversible-decision anchor required (contrast /foundational-review). Triggers: '/readiness-audit <scope-root> --for "<event>"', '/audit-ready', 'readiness audit', 'release-readiness audit', 'is this ready to ship/publish/hand over', 'public-release audit'. (Code port — ADR-094.)
release-audit
Release & supply-chain readiness audit: gathers evidence from real workflows, manifests, and repo settings, compares against a gold-standard reference stack, has an adversarial subagent try to refute the draft, and returns a prioritized action plan (P1–P3) whose fixes are delegated to the sibling setup skills. Use when asked to audit release automation, publishing security, CI or supply-chain maturity, or whether a repo is ready to release. For a whole-repo health check (docs, tests, code quality) use maturity-analysis instead.
agent-readiness-audit
Audit whether AI agents can actually use your product — docs, APIs, onboarding, errors, and discoverability, evaluated from a non-human user's perspective. Use when asked if a product is agent-ready, to audit a site or API for AI usability, to prepare for agentic traffic, or when agents keep failing against your product. Produces a scored readiness report with per-surface findings and a prioritised fix list. For optimising a single article for AI citation use aeo-optimizer; for designing the MCP server itself use mcp-server-spec.