GS

gsd-plan-review-convergence

Iteratively replans development tasks based on feedback.

Install

mkdir -p .claude/skills/gsd-plan-review-convergence && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16541" && unzip -o skill.zip -d .claude/skills/gsd-plan-review-convergence && rm skill.zip

Installs to .claude/skills/gsd-plan-review-convergence

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Cross-AI plan convergence loop — replan with review feedback until no HIGH concerns remain.
91 charsno explicit “when” trigger
Advanced

Key capabilities

  • Replan with review feedback
  • Check for HIGH concerns in plans
  • Orchestrate plan review with external AI CLIs
  • Spawn agents for existing skills
  • Detect and escalate stall conditions

How it works

The skill repeatedly reviews plans with external AI CLIs, replanning with feedback until no HIGH concerns remain or a maximum cycle limit is reached.

Inputs & outputs

You give it
Plan with review feedback and optional CLI reviewer flags
You get back
Converged plan with no HIGH concerns or an escalation report

When to use gsd-plan-review-convergence

  • Converging development plans
  • Resolving planning concerns
  • Re-planning based on feedback

About this skill

<codex_skill_adapter>

A. Skill Invocation

  • This skill is invoked by mentioning $gsd-plan-review-convergence.
  • Treat all user text after $gsd-plan-review-convergence 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:

  • headerheader
  • questionquestion
  • 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 or unavailable, you MUST stop and present the questions as a plain-text numbered list, then wait for the user's reply. Do NOT pick a default and continue (#3018).
  • You may only proceed without a user answer when one of these is true: (a) the invocation included an explicit non-interactive flag (--auto or --all), (b) the user has explicitly approved a specific default for this question, or (c) the workflow's documented contract says defaults are safe (e.g. autonomous lifecycle paths).
  • Do NOT write workflow artifacts (CONTEXT.md, DISCUSSION-LOG.md, PLAN.md, checkpoint files) until the user has answered the plain-text questions or one of (a)-(c) above applies. Surfacing the questions and waiting is the correct response — silently defaulting and writing artifacts is the #3018 failure mode.

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>
<objective> Cross-AI plan convergence loop — an outer revision gate around gsd-review and gsd-planner. Repeatedly: review plans with external AI CLIs → if HIGH concerns found → replan with --reviews feedback → re-review. Stops when no HIGH concerns remain or max cycles reached.

Flow: Agent→Skill("gsd-plan-phase") → Agent→Skill("gsd-review") → check HIGHs → Agent→Skill("gsd-plan-phase --reviews") → Agent→Skill("gsd-review") → ... → Converge or escalate

Replaces gsd-plan-phase's internal gsd-plan-checker with external AI reviewers (codex, gemini, etc.). Each step runs inside an isolated Agent that calls the corresponding existing Skill — orchestrator only does loop control.

Orchestrator role: Parse arguments, validate phase, spawn Agents for existing Skills, check HIGHs, stall detection, escalation gate. </objective>

<execution_context> @/Volumes/External/ColourWithin/dot-github/.codex/get-shit-done/workflows/plan-review-convergence.md @/Volumes/External/ColourWithin/dot-github/.codex/get-shit-done/references/revision-loop.md @/Volumes/External/ColourWithin/dot-github/.codex/get-shit-done/references/gates.md @/Volumes/External/ColourWithin/dot-github/.codex/get-shit-done/references/agent-contracts.md </execution_context>

<runtime_note> Copilot (VS Code): Use vscode_askquestions wherever this workflow calls AskUserQuestion. They are equivalent — vscode_askquestions is the VS Code Copilot implementation of the same interactive question API. Do not skip questioning steps because AskUserQuestion appears unavailable; use vscode_askquestions instead. </runtime_note>

<context> Phase number: extracted from {{GSD_ARGS}} (required)

Flags:

  • --codex — Use Codex CLI as reviewer (default if no reviewer specified)
  • --gemini — Use Gemini CLI as reviewer
  • --claude — Use the agent CLI as reviewer (separate session)
  • --opencode — Use OpenCode as reviewer
  • --ollama — Use local Ollama server as reviewer (OpenAI-compatible, default host http://localhost:11434; configure model via review.models.ollama)
  • --lm-studio — Use local LM Studio server as reviewer (OpenAI-compatible, default host http://localhost:1234; configure model via review.models.lm_studio)
  • --llama-cpp — Use local llama.cpp server as reviewer (OpenAI-compatible, default host http://localhost:8080; configure model via review.models.llama_cpp)
  • --all — Use all available CLIs and running local model servers
  • --max-cycles N — Maximum replan→review cycles (default: 3)

Feature gate: This command requires workflow.plan_review_convergence=true. Enable with: gsd config-set workflow.plan_review_convergence true </context>

<process> Execute end-to-end. Preserve all workflow gates (pre-flight, revision loop, stall detection, escalation). </process>

When not to use it

  • When no HIGH concerns remain in the plan
  • When the maximum number of cycles is reached
  • When the task is not related to plan review or convergence

Limitations

  • Stops when no HIGH concerns remain
  • Stops when max cycles reached
  • Requires `workflow.plan_review_convergence=true`

How it compares

This skill automates a convergence loop for plan review, integrating feedback from multiple AI CLIs to refine plans iteratively, which is more efficient than manual review cycles.

Compared to similar skills

gsd-plan-review-convergence side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
gsd-plan-review-convergence (this skill)03moNo flagsAdvanced
trello413moReviewBeginner
executing-plans63moNo flagsIntermediate
github-project-management46moReviewAdvanced

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