gsd-eval-review

name	gsd-eval-review
description	Retroactively audit an executed AI phase's evaluation coverage — scores each eval dimension as COVERED/PARTIAL/MISSING and produces an actionable EVAL-REVIEW.md with remediation plan
metadata	{"short-description":"Retroactively audit an executed AI phase's evaluation coverage — scores each eval dimension as COVERED/PARTIAL/MISSING and produces an actionable EVAL-REVIEW.md with remediation..."}

<codex_skill_adapter>

A. Skill Invocation

• This skill is invoked by mentioning $gsd-eval-review.
• Treat all user text after $gsd-eval-review as {{GSD_ARGS}}.
• If no arguments are present, treat {{GSD_ARGS}} as empty.

B. AskUserQuestion → request_user_input Mapping

GSD workflows use AskUserQuestion (Claude Code syntax). Translate to Codex request_user_input:

Parameter mapping:

• header → header
• question → question
• Options formatted as "Label" — description → {label: "Label", description: "description"}
• Generate id from header: lowercase, replace spaces with underscores

Batched calls:

• AskUserQuestion([q1, q2]) → single request_user_input with multiple entries in questions[]

Multi-select workaround:

• Codex has no multiSelect. Use sequential single-selects, or present a numbered freeform list asking the user to enter comma-separated numbers.

Execute mode fallback:

• When request_user_input is rejected (Execute mode), present a plain-text numbered list and pick a reasonable default.

C. Task() → spawn_agent Mapping

GSD workflows use Task(...) (Claude Code syntax). Translate to Codex collaboration tools:

Direct mapping:

• Task(subagent_type="X", prompt="Y") → spawn_agent(agent_type="X", message="Y")
• Task(model="...") → omit. spawn_agent has no inline model parameter; GSD embeds the resolved per-agent model directly into each agent's .toml at install time so model_overrides from .planning/config.json and ~/.gsd/defaults.json are honored automatically by Codex's agent router.
• fork_context: false by default — GSD agents load their own context via <files_to_read> blocks

Spawn restriction:

• Codex restricts spawn_agent to cases where the user has explicitly requested sub-agents. When automatic spawning is not permitted, do the work inline in the current agent rather than attempting to force a spawn.

Parallel fan-out:

• Spawn multiple agents → collect agent IDs → wait(ids) for all to complete

Result parsing:

• Look for structured markers in agent output: CHECKPOINT, PLAN COMPLETE, SUMMARY, etc.
• close_agent(id) after collecting results from each agent </codex_skill_adapter>

Conduct a retroactive evaluation coverage audit of a completed AI phase. Checks whether the evaluation strategy from AI-SPEC.md was implemented. Produces EVAL-REVIEW.md with score, verdict, gaps, and remediation plan.

<execution_context> @/Users/andreas/Library/Mobile Documents/comappleCloudDocs/Code/gsd-test/.codex/get-shit-done/workflows/eval-review.md @/Users/andreas/Library/Mobile Documents/comappleCloudDocs/Code/gsd-test/.codex/get-shit-done/references/ai-evals.md </execution_context>

Phase: {{GSD_ARGS}} — optional, defaults to last completed phase. Execute @/Users/andreas/Library/Mobile Documents/com~apple~CloudDocs/Code/gsd-test/.codex/get-shit-done/workflows/eval-review.md end-to-end. Preserve all workflow gates.