PRP Loop
Wirasm/prp
Runs the plan, implement and review pipeline detached in fresh headless sessions, looping review and fix until the pull request is clean.
[OMX] Strict autonomous loop: $deep-interview - $ralplan - $ultragoal (+ $team if needed) - $code-review - $ultraqa
$ npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yangyuan-zhen/PolyWeather autopilot --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/autopilot .claude/skills/autopilot && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "autopilot" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/autopilot into .claude/skills/autopilot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autopilot", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/autopilotType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yangyuan-zhen/PolyWeather autopilot --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.codex/skills/autopilot .agents/skills/autopilot && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "autopilot" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/autopilot into .agents/skills/autopilot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autopilot", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yangyuan-zhen/PolyWeather autopilot --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.codex/skills/autopilot .cursor/skills/autopilot && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "autopilot" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/autopilot into .cursor/skills/autopilot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autopilot", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/yangyuan-zhen/PolyWeather.git --path .codex/skills/autopilot--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yangyuan-zhen/PolyWeather autopilot --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.codex/skills/autopilot .gemini/skills/autopilot && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "autopilot" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/autopilot into .gemini/skills/autopilot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autopilot", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install yangyuan-zhen/PolyWeather autopilotInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .github/skills && cp -r skills-src/.codex/skills/autopilot .github/skills/autopilot && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "autopilot" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/autopilot into .github/skills/autopilot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autopilot", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install yangyuan-zhen/PolyWeather autopilot --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.codex/skills/autopilot .opencode/skills/autopilot && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "autopilot" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/autopilot into .opencode/skills/autopilot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autopilot", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
autopilot[OMX] Strict autonomous loop: $deep-interview - $ralplan - $ultragoal (+ $team if needed) - $code-review - $ultraqa
Autopilot is an agent skill from yangyuan-zhen/PolyWeather. [OMX] Strict autonomous loop: $deep-interview - $ralplan - $ultragoal (+ $team if needed) - $code-review - $ultraqa
Its SKILL.md is about 5.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering Autonomous loops and Code review. The repository describes itself as: polymarket Intelligent Weather Quant Analysis Bot. The licence is AGPL-3.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 43e658b. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are json and bash).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Autopilot loads about 5.8k tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 2,383 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from yangyuan-zhen/PolyWeather at commit 43e658b, republished under its AGPL-3.0 licence (© yangyuan-zhen). 2,383 words, ~5,806 tokens.
.claude/skills/autopilot/SKILL.md (or your agent's skills folder).<Purpose>
Autopilot is the strict autonomous delivery loop for non-trivial work. Its recommended/default contract is exactly:
$deep-interview -> $ralplan -> $ultragoal (+ $team if needed) -> $code-review -> $ultraqaIf $code-review or $ultraqa is not clean, Autopilot returns to $ralplan with the findings as the next planning input, then continues again through $ultragoal, $code-review, and $ultraqa until the gates are clean or a hard blocker is reported. Ralph is a legacy/explicit alternate execution loop only; do not advertise Ralph as the default Autopilot path.
</Purpose>
<Use_When>
$autopilot, "autopilot", "auto pilot", "autonomous", "build me", "create me", "make me", "full auto", "handle it all", or "I want a/an..."<Do_Not_Use_When>
$plan / $ralplan$ultragoal, $ralph only when explicitly requested, or direct executor work$code-review
</Do_Not_Use_When><Strict_Loop_Contract> Autopilot must not run a separate broad expansion/planning/execution/QA/validation lifecycle as its primary behavior. It delegates those concerns to the canonical workflow phases below:
Phase deep-interview — Socratic requirements clarification gate
$deep-interview to clarify intent, scope, non-goals, constraints, and decision boundaries.max_rounds is a cap, not a target.omx question, re-score ambiguity against the active profile threshold. Ask another question only when a readiness gate is still unresolved and the answer would materially change execution; otherwise crystallize the spec and hand off.$ralplan, including an explicit interview-complete rationale when leaving deep-interview.Phase ralplan — consensus planning gate
planning_routing in state before heavy planning. When the Autopilot/main model resolves to a cheap/mini lane (for example o4-mini, *-mini, *spark*, or an explicitly cheap/economy/lite model name), the initial planning/decomposition owner is dedicated [planner]; otherwise [main] may keep ownership for backward compatibility. A configured agentModels.planner is an explicit opt-in that forces dedicated [planner] ownership even when [main] is not cheap/mini.$ralplan to produce/update PRD and test-spec artifacts. If planning_routing.owner is planner, use the dedicated [planner] role for the initial Planner draft/decomposition before the Architect→Critic consensus gates.ralplan_consensus_gate.complete:false and blocked_reason:"documented_host_consensus_receipt_unavailable".Architect approval first and subsequent Critic approval second. These ordered reviews remain lifecycle evidence only and never replace the official host receipt.return_to_ralplan_reason and the findings as first-class planning input.ralplan or report an explicit blocker/max-iteration outcome; do not progress to $ultragoal, $team, $ralph, or implementation.ralplan_consensus_gate.complete:true. Without that receipt, remain in ralplan and report the host blocker.Phase ultragoal — durable implementation + verification loop
$ultragoal only from ralplan artifacts whose consensus gate is authorized by a verified official host receipt..omx/ultragoal ledger checkpoints, implementation, tests, build/lint/typecheck evidence, cleanup, and final review gate discipline.$team only inside an active Ultragoal story when the story clearly benefits from coordinated parallel execution (for example independent file/module lanes, broad test matrix work, or multi-domain implementation). Team remains explicit and leader-owned; Ultragoal keeps the goal/ledger state.$code-review.Phase code-review — merge-readiness gate
$code-review on the diff/artifacts produced by $ultragoal.APPROVE with architectural status CLEAR.COMMENT, REQUEST CHANGES, any architectural WATCH/BLOCK, or any unresolved finding is not clean.review_verdict, set current_phase:"rework", and carry the findings as the sanctioned execution-fix input. Return to Phase ralplan only when the review shows the plan/requirements are wrong or incomplete.Phase ultraqa — adversarial QA gate
$ultraqa after a clean code review when user-facing behavior, workflows, CLI/runtime behavior, integration surfaces, or regression risk warrant adversarial QA.ultraqa as skipped with an explicit condition and evidence.return_to_ralplan_reason, and transition back to Phase ralplan.The only normal terminal state is complete after clean code review and a passed or explicitly skipped UltraQA gate. Cancellation, blocked credentials, unrecoverable repeated failures, or explicit user stop may terminate earlier with preserved state.
</Strict_Loop_Contract>
<Pre-context Intake>
Before Phase deep-interview or ralplan starts or resumes:
.omx/context/{slug}-*.md snapshot when available..omx/context/{slug}-{timestamp}.md (UTC YYYYMMDDTHHMMSSZ) with:activation-prompt, legacy-unverified, or unavailable)explore first before or during $deep-interview ($deep-interview --quick <task> remains acceptable for bounded low-ambiguity intake); do not skip the clarification gate merely because the task sounds actionable.<Execution_Policy>
deep-interview, then ralplan, then ultragoal, then code-review, then ultraqa.$team is conditional and explicit: use it only within an Ultragoal story when parallel execution materially improves throughput, quality, or safety.$deep-interview and $ralplan.$code-review that requires implementation repair enters Phase rework; a non-clean review that changes the plan/requirements, or failed $ultraqa, returns to $ralplan..omx/state, $deep-interview, $ralplan, $ultragoal, optional $team, $code-review, $ultraqa, and pipeline primitives; do not invent a separate execution framework.$ralph as an intentional alternate execution phase, but do not present it as Autopilot's default recommended loop.<State_Management>
Use the CLI-first state surface (omx state ... --json) for Autopilot lifecycle state. State must be session-aware when a session id exists. If the explicit MCP compatibility surface is already available, equivalent omx_state tool calls remain acceptable but are not required.
Inside active Autopilot, named child phases such as $ralplan are supervised phases, not peer workflow activations: keep mode:"autopilot" active and update current_phase:"ralplan" rather than starting standalone mode:"ralplan" over Autopilot.
Required fields:
{
"mode": "autopilot",
"active": true,
"current_phase": "deep-interview",
"iteration": 1,
"review_cycle": 0,
"max_iterations": 10,
"phase_cycle": ["deep-interview", "ralplan", "ultragoal", "code-review", "ultraqa"],
"handoff_artifacts": {
"context_snapshot_path": ".omx/context/<slug>-<timestamp>.md",
"deep_interview": null,
"ralplan": null,
"ralplan_consensus_gate": {
"required": true,
"sequence": ["architect-review", "critic-review"],
"planning_artifacts_are_not_consensus": true,
"required_review_roles": ["architect", "critic"],
"ralplan_architect_review": null,
"ralplan_critic_review": null,
"complete": false
},
"ultragoal": null,
"code_review": null,
"ultraqa": null
},
"review_verdict": null,
"qa_verdict": null,
"return_to_ralplan_reason": null
}omx state write --input '{"mode":"autopilot","active":true,"current_phase":"deep-interview","iteration":1,"review_cycle":0,"state":{"phase_cycle":["deep-interview","ralplan","ultragoal","code-review","ultraqa"],"handoff_artifacts":{"context_snapshot_path":"<snapshot-path>","deep_interview":null,"ralplan":null,"ralplan_consensus_gate":{"required":true,"sequence":["architect-review","critic-review"],"planning_artifacts_are_not_consensus":true,"required_review_roles":["architect","critic"],"ralplan_architect_review":null,"ralplan_critic_review":null,"complete":false},"ultragoal":null,"code_review":null,"ultraqa":null},"review_verdict":null,"qa_verdict":null,"return_to_ralplan_reason":null}}' --jsondeep_interview_gate:{"status":"complete","rationale":"<why requirements are complete>","handoff_summary":"<summary>"} (or equivalent non-empty rationale/summary) plus the clarified spec/requirements under handoff_artifacts.deep_interview; if a final omx question was involved, keep its same-session answered record linked by question_id/satisfied_at. For skip, persist deep_interview_gate:{"status":"skipped","skip_authorized_by_user":true,"skip_reason":"<user-authorized reason>","skipped_at":"<timestamp>","source":"user","session_id":"<session>"}. Do not leave deep-interview merely because the first omx question was answered or cleared.<!-- OMX:AUTOPILOT:DEEP-INTERVIEW-RALPLAN-HANDOFF:v1 --> marker immediately precedes the executable completion handoff fence; automation may locate exactly that fence.<!-- OMX:AUTOPILOT:DEEP-INTERVIEW-RALPLAN-HANDOFF:v1 -->
omx state write --input '{"mode":"autopilot","active":true,"current_phase":"ralplan","session_id":"'"${OMX_SESSION_ID:?authoritative OMX session required}"'","workingDirectory":"'"${PWD:?working directory required}"'","state":{"deep_interview_gate":{"status":"complete","rationale":"requirements are clarified and ready for planning","handoff_summary":"durable deep-interview handoff recorded for ralplan"},"handoff_artifacts":{"deep_interview":".omx/specs/deep-interview-handoff.md"}}}' --jsonowner_omx_session_id, codex_session_id, and owner_codex_session_id must each equal session_id.execution_contract_required:true, persist a complete structured execution_contract under handoff_artifacts.deep_interview before leaving deep-interview. The canonical schema is version:1, execution_stride:"task"|"deliverable"|"milestone", source:"deep-interview", selected_by:"user"|"default", allow_task_shrink:<boolean>, non-empty completion_unit, non-empty stop_condition, acceptance_coverage_scope:"task"|"deliverable"|"milestone", and shrink_policy:"allowed"|"ask_before_shrink"|"deny_unless_blocked".execution_contract_required:true: task means allow_task_shrink:true, acceptance_coverage_scope:"task", shrink_policy:"allowed"; deliverable means allow_task_shrink:false, acceptance_coverage_scope:"deliverable", shrink_policy:"ask_before_shrink"; milestone means allow_task_shrink:false, acceptance_coverage_scope:"milestone", shrink_policy:"deny_unless_blocked".execution_contract_required is absent or false. Do not infer stride from prose, broadness, phase names, snapshots, or task size; this foundation only validates an explicit structured contract and deliberately uses milestone rather than phase. New artifacts must write canonical snake_case keys under handoff_artifacts.deep_interview; the runtime may read legacy camelCase field/marker aliases and direct/nested execution_contract locations only as compatibility input.ralplan_consensus_gate.complete:true from an official host-issued receipt verified through a documented non-user-mintable host surface. Native-subagent Architect/Critic lanes, tracker records, codex_exec, and artifact approvals are lifecycle or trace evidence only. Until that verifier exists, keep current_phase:"ralplan" and persist blocked_reason:"documented_host_consensus_receipt_unavailable".current_phase:"ralplan", persist ralplan_consensus_gate.complete:false with blocked_reason, and report an explicit blocker or max-iteration outcome instead of handing off to execution.current_phase:"code-review", persist implementation/test/ledger evidence under handoff_artifacts.ultragoal.current_phase:"ultraqa" only after a real $code-review stage/subagent has produced durable evidence; persist the clean review under handoff_artifacts.code_review with its source thread/tool/stage reference. Do not author review_verdict:{clean:true} from the leader's own summary.review_cycle, set current_phase:"rework", persist review_verdict, persist the phase handoff under handoff_artifacts.code_review, and keep the fix scoped to the review findings before returning to code-review.active:false, current_phase:"complete", persist review_verdict:{recommendation:"APPROVE", architectural_status:"CLEAR", clean:true}, qa_verdict:{clean:true, skipped:<boolean>, reason:<string|null>}, and completed_at only when both gates have durable source evidence. Required evidence is either (a) actual $code-review/$ultraqa stage or native-subagent/thread/tool records, or (b) for QA only, an explicit persisted skip reason for a documented docs-only/trivially non-runtime condition. If that evidence is missing, keep the active phase at code-review or ultraqa and record a blocker instead of self-attesting a clean gate.iteration and review_cycle, set current_phase:"ralplan", persist review_verdict or qa_verdict, persist the phase handoff, and set return_to_ralplan_reason to a concise findings-driven reason.ralph; preserve and resume them rather than rewriting history to Ultragoal.$cancel; preserve progress for resume rather than deleting handoff artifacts.
</State_Management><Continuation_And_Resume>
When the user says continue, resume, or keep going while Autopilot is active, read autopilot-state.json and continue from current_phase:
deep-interview: clarify requirements and record the handoff artifact.ralplan: run/update consensus planning from current handoffs and any return_to_ralplan_reason.ultragoal: execute the approved plan durably and record verification/ledger evidence.rework: perform only the implementation fixes required by the current code-review findings, record fresh implementation/verification evidence, and return to code-review.team: continue explicit team work only when it is nested under the active Ultragoal story and report evidence back to the leader.code-review: review the current diff and decide clean vs return-to-ralplan.ultraqa: run or explicitly skip adversarial QA based on the documented condition, then finish if clean or transition to ralplan with findings if not clean.ralph: resume only for explicit legacy Ralph-path Autopilot state.complete: report completion evidence; do not restart.Do not restart discovery or discard handoff artifacts on continuation. </Continuation_And_Resume>
<Pipeline_Orchestrator>
Autopilot may be represented by the configurable pipeline orchestrator (src/pipeline/) when useful. The default Autopilot pipeline contract is:
deep-interview -> ralplan -> ultragoal -> code-review -> ultraqaPipeline state should use current_phase values that match the same phase names (deep-interview, ralplan, ultragoal, rework, code-review, ultraqa, complete, failed) and should carry iteration, review_cycle, handoff_artifacts, review_verdict, qa_verdict, and return_to_ralplan_reason alongside stage results. $team is not a default pipeline stage; it is an explicit conditional execution engine inside an Ultragoal story.
</Pipeline_Orchestrator>
<Escalation_And_Stop_Conditions>
$cancel.$code-review is clean and $ultraqa has passed or been explicitly skipped with evidence.
</Escalation_And_Stop_Conditions><Final_Checklist>
deep-interview produced/updated clarified requirements or a concise specralplan produced/updated planning artifacts and preserved subsequent Architect→Critic approvals as lifecycle-only evidence; it advanced only with a verified official host receipt, or remained in ralplan with complete:false and blocked_reason:"documented_host_consensus_receipt_unavailable".ultragoal implemented and verified the plan with fresh evidence and durable ledger/checkpoint referencesrework was used for implementation-only review fixes when applicable, with findings scoped to a fresh code-review cycle$team was used only if the active Ultragoal story needed coordinated parallel work, or explicitly recorded as not neededcode-review returned a clean verdict (APPROVE + CLEAR)ultraqa passed, or was explicitly skipped because the change was docs-only/trivially non-runtime with evidencereview_verdict cites durable source evidence from a real $code-review stage/subagent/thread/tool record; qa_verdict cites durable $ultraqa evidence or an explicit persisted low-risk skip reason; leader-authored summaries alone are not gate evidencereview_verdict.clean is true, qa_verdict.clean is true, and return_to_ralplan_reason is nullcomplete or cancellation state is preserved coherently<Examples>
<Good>
User: `$autopilot implement GitHub issue #42`
Flow: create/load context snapshot -> `$deep-interview` requirements check -> `$ralplan` issue plan -> `$ultragoal` durable implementation + tests (launch `$team` only if a story needs parallel lanes) -> `$code-review` -> `$ultraqa`; if review or QA requests changes, return to `$ralplan` with findings.
</Good>
<Good>
User: `continue`
Context: Autopilot state says `current_phase:"code-review"`.
Flow: run `$code-review` on current diff, persist verdict, transition to `ultraqa` if clean or to `ralplan` with findings if not clean.
</Good>
<Good>
User: `$autopilot --legacy-ralph finish the migration`
Flow: preserve the explicit legacy Ralph execution choice and run the old Ralph execution lane as an alternate, without changing the documented default Autopilot recommendation.
</Good>
<Bad>
Autopilot invents independent "Expansion", "QA", and "Validation" phases and treats them as the primary lifecycle.
Why bad: this bypasses the strict `$deep-interview -> $ralplan -> $ultragoal -> $code-review -> $ultraqa` contract.
</Bad>
</Examples>
© yangyuan-zhen, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .codex/skills/autopilot of yangyuan-zhen/PolyWeather.
Open the folder on GitHubat commit 43e658b
Autopilot next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Autopilot this skillyangyuan-zhen/PolyWeather | 316 | — | ~5.8k | Automated safety check: Pass | AGPL-3.0 | |
| PRP LoopWirasm/prp | 2.3k | — | ~894 | Automated safety check: Pass | MIT | |
| Autoresearchleo-kuang-ai/spec-first | 107 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Copilot PR Autopilotgithub/awesome-copilot | 40k | — | ~3.4k | Automated safety check: Pass | MIT | |
| O2 Review Loopopenobserve/openobserve | 22k | — | ~3.7k | Automated safety check: Pass | AGPL-3.0 | |
| Autoresearch Iteration Loopuditgoenka/autoresearch | 6.5k | 1 repos | ~2k | Automated safety check: Pass | MIT |
Wirasm/prp
Runs the plan, implement and review pipeline detached in fresh headless sessions, looping review and fix until the pull request is clean.
leo-kuang-ai/spec-first
Autonomous goal-directed iteration loop: modify, verify, keep/discard against a metric or a checkable success predicate, with bounded cycles, plateau/ceiling backstops, safety-screened commands, and…
github/awesome-copilot
Copilot left 14 review comments on your PR — half are nits. An agent skill from github/awesome-copilot.
openobserve/openobserve
Splits a change into planner, coder and independent reviewer roles: you confirm a spec, a subagent implements it, and a separate reviewer checks each round's local WIP commit.
uditgoenka/autoresearch
Runs an autonomous modify, verify, keep-or-discard loop against any metric, with subcommands for planning, debugging, fixing, security audits, shipping and more.
cobusgreyling/loop-engineering
Installs Loop Engineering into a project through the single @cobusgreyling/loop CLI, scaffolding a report-only loop and a readiness score.
yangyuan-zhen/PolyWeather
[OMX] Run an anti-slop cleanup/refactor/deslop workflow. An agent skill from yangyuan-zhen/PolyWeather.
yangyuan-zhen/PolyWeather
[OMX] Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries.
yangyuan-zhen/PolyWeather
[OMX] Stateful validator-gated research loop with native-hook persistence
yangyuan-zhen/PolyWeather
[OMX] Bounded best-practice research wrapper using official/upstream evidence first
yangyuan-zhen/PolyWeather
[OMX] Cancel any active OMX mode (autopilot, ralph, ultrawork, ecomode, ultraqa, swarm, ultrapilot, pipeline, team)
yangyuan-zhen/PolyWeather
[OMX] Configure OMX notifications - unified entry point for all platforms
Categories
[OMX] Strict autonomous loop: $deep-interview - $ralplan - $ultragoal (+ $team if needed) - $code-review - $ultraqa. Autopilot is an agent skill from yangyuan-zhen/PolyWeather.
Autopilot fits situations like: tasks that involve Autonomous loops; tasks that involve Code review.
Run `npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a claude-code`. Or copy the skill folder (.codex/skills/autopilot in yangyuan-zhen/PolyWeather) into .claude/skills/autopilot in your project. Claude Code loads it when a task matches its description.
Run `npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a codex`. Or copy the skill folder (.codex/skills/autopilot in yangyuan-zhen/PolyWeather) into .agents/skills/autopilot in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yangyuan-zhen/PolyWeather --skill autopilot -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autopilot, .gemini/skills/autopilot, .github/skills/autopilot and .opencode/skills/autopilot in your project.
SKILL.md names no scripts, command-line tools or credentials: Autopilot is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Autopilot is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.8k tokens (SKILL.md is roughly 23k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Autopilot: PRP Loop (Wirasm/prp, 2.3k stars), Autoresearch (leo-kuang-ai/spec-first, 107 stars), Copilot PR Autopilot (github/awesome-copilot, 40k stars) and O2 Review Loop (openobserve/openobserve, 22k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
yangyuan-zhen (a GitHub user) maintains it in yangyuan-zhen/PolyWeather, which has 316 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on September 20, 2026.
Source: yangyuan-zhen/PolyWeather on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.