Ralph
Yeachan-Heo/oh-my-claudecode
Self-referential loop until task completion with configurable verification reviewer
[OMX] Self-referential loop until task completion with architect verification
$ npx skills add yangyuan-zhen/PolyWeather --skill ralph -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yangyuan-zhen/PolyWeather ralph --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/ralph .claude/skills/ralph && 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 "ralph" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/ralph into .claude/skills/ralph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ralph", 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/ralphType 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 ralph -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yangyuan-zhen/PolyWeather ralph --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/ralph .agents/skills/ralph && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ralph" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/ralph into .agents/skills/ralph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ralph", 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 ralph -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yangyuan-zhen/PolyWeather ralph --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/ralph .cursor/skills/ralph && 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 "ralph" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/ralph into .cursor/skills/ralph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ralph", 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/ralph--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 ralph -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yangyuan-zhen/PolyWeather ralph --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/ralph .gemini/skills/ralph && 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 "ralph" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/ralph into .gemini/skills/ralph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ralph", 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 ralphInstalls 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 ralph -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/ralph .github/skills/ralph && 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 "ralph" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/ralph into .github/skills/ralph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ralph", 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 ralph -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 ralph --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/ralph .opencode/skills/ralph && 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 "ralph" agent skill from https://github.com/yangyuan-zhen/PolyWeather/tree/main/.codex/skills/ralph into .opencode/skills/ralph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ralph", 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.
ralph[OMX] Self-referential loop until task completion with architect verification
Ralph is an agent skill from yangyuan-zhen/PolyWeather. [OMX] Self-referential loop until task completion with architect verification
Its SKILL.md is about 5.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: polymarket Intelligent Weather Quant Analysis Bot. The licence is AGPL-3.0.
8 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.
Shell commands in SKILL.md call:
makeFrom 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.
Ralph loads about 5.7k tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 2,685 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). 2,685 words, ~5,727 tokens.
.claude/skills/ralph/SKILL.md (or your agent's skills folder).[RALPH + ULTRAWORK - ITERATION {{ITERATION}}/{{MAX}}]
Your previous attempt did not output the completion promise. Continue working on the task.
<Purpose>
Ralph is a persistence loop that keeps working on a task until it is fully complete and architect-verified. It wraps ultrawork's parallel execution with session persistence, automatic retry on failure, and mandatory verification before completion.
</Purpose>
<Use_When>
<Do_Not_Use_When>
autopilot insteadplan skill insteadultrawork directly
</Do_Not_Use_When><Why_This_Exists> Complex tasks often fail silently: partial implementations get declared "done", tests get skipped, edge cases get forgotten. Ralph prevents this by looping until work is genuinely complete, requiring fresh verification evidence before allowing completion, and using explicit architect native-subagent verification to confirm quality. </Why_This_Exists>
<Execution_Policy>
run_in_background: true for long operations (installs, builds, test suites)omx ralplan preflight --json only when native role routing reports role_routing_unavailable and Ralph attempts adapted Ralplan Planner, Architect, or Critic authority, adapted role-intent, or adapted consensus authority. On unsupported_documented_leader_proof, stop before that adapted authority and use a Codex surface with documented root proof or a reviewed alternative workflow. Do not infer root authority from session_id, undocumented thread_id, session/pointer/transcript/cwd state, absent child data, or prompt labels. Ordinary native planning, lifecycle, state, status, health, HUD, runtime, setup, install, sync, and unrelated delegation remain outside this preflight boundary and under their existing controls.agent_type role routing, set agent_type to an installed OMX role and never omit it for OMX work; use reasoning_effort for per-dispatch intensity when needed.role_routing_unavailable, do not fabricate agent_type. On the exact reviewed Codex releases 0.144.5, 0.145.0, 0.146.1, and 0.148.0-alpha.5, only an attempted adapted Ralplan Planner, Architect, Critic, role-intent, or consensus authority path requires omx ralplan preflight --json and fails closed on unsupported_documented_leader_proof; every other version remains unknown and fails closed. Do not use prompt labels, task-name carriers, pending intents, markers, or omx ralplan role-intent write as substitutes.low, STANDARD -> medium, THOROUGH -> xhighget_goal, preserve it as the top-level stop condition, and only call update_goal({status: "complete"}) after a Ralph completion audit proves the objective is actually achieved.
</Execution_Policy><Steps>
0. **Pre-context intake (required before planning/execution loop starts)**:
- Assemble or load a context snapshot at `.omx/context/{task-slug}-{timestamp}.md` (UTC `YYYYMMDDTHHMMSSZ`).
- Minimum snapshot fields:
- task statement
- desired outcome
- known facts/evidence
- constraints
- unknowns/open questions
- likely codebase touchpoints
- If an existing relevant snapshot is available, reuse it and record the path in Ralph state.
- If request ambiguity is high, gather brownfield facts first. `omx explore` is deprecated; use normal repository inspection tools/subagents for simple read-only repository lookups and `omx sparkshell` only for explicit shell-native read-only evidence. Then run `$deep-interview --quick <task>` to close critical gaps.
- Do not begin Ralph execution work (delegation, implementation, or verification loops) until snapshot grounding exists. If forced to proceed quickly, note explicit risk tradeoffs.
- A Ralplan-originated handoff alone does not require preflight. Before intake, run `omx ralplan preflight --json` only when native role routing is unavailable and the handoff attempts adapted Ralplan Planner, Architect, Critic, role-intent, or consensus authority. On `unsupported_documented_leader_proof`, record the reason in Execution Policy and stop before that authority; otherwise follow the existing intake controls.
1. **Review progress**: Check TODO list and any prior iteration state
2. **Continue from where you left off**: Pick up incomplete tasks
3. **Delegate in parallel**: Route tasks to specialist native agents with explicit `agent_type` and appropriate `reasoning_effort`
- Simple lookups: `reasoning_effort="low"` -- "What does this function return?"
- Standard work: `reasoning_effort="medium"` -- "Add error handling to this module"
- Complex analysis: `reasoning_effort="xhigh"` -- "Debug this race condition"
- When Ralph is entered as a ralplan follow-up, start from the approved **available-agent-types roster** and make the delegation plan explicit: implementation lane, evidence/regression lane, and final sign-off lane using only known agent types
4. **Run long operations in background**: Builds, installs, test suites use `run_in_background: true`
5. **Visual task gate (when screenshot/reference images are present)**:
- Run the Visual Ralph verdict step **before every next edit**.
- Require structured JSON output: `score`, `verdict`, `category_match`, `differences[]`, `suggestions[]`, `reasoning`.
- Persist verdict to `.omx/state/{scope}/ralph-progress.json` including numeric + qualitative feedback.
- Default pass threshold: `score >= 90`.
- **URL-based visual cloning tasks**: When the task description contains a target URL (e.g., "clone https://example.com"), route the work through `$visual-ralph`. `$web-clone` is hard-deprecated; Visual Ralph owns the migrated live-URL visual implementation use case and uses its built-in visual verdict step for measured visual scoring.
6. **Verify completion with fresh evidence**:
- If Codex goal mode is available, call `get_goal` before final verification to restate the active objective and include it in the evidence checklist.
a. Identify what command proves the task is complete
b. Run verification (test, build, lint)
c. Read the output -- confirm it actually passed
d. Check: zero pending/in_progress TODO items
7. **Architect verification** (native role):
- <5 files, <100 lines with full tests: `task(agent_type="architect", reasoning_effort="medium", prompt="...")` minimum
- Standard changes: `task(agent_type="architect", reasoning_effort="medium", prompt="...")`
- >20 files or security/architectural changes: `task(agent_type="architect", reasoning_effort="xhigh", prompt="...")`
- Ralph floor: always run an explicit `architect` native subagent, even for small changes
- On `role_routing_unavailable`, do not invoke `omx ralplan role-intent write` or manufacture an Architect identity. Run the documented-leader preflight only if Architect verification would attempt adapted Ralplan Architect authority; on the exact reviewed Codex releases 0.144.5, 0.145.0, 0.146.1, and 0.148.0-alpha.5 that adapted path is unavailable, while every other version remains unknown and fails closed. Surface the leader-proof diagnostic and the supported-surface recovery guidance, then stop before that authority. Ordinary Ralph delegation remains under its existing controls. Use an adapted route only after its documented positive root proof has been reviewed and implemented.
7.5 **Mandatory Deslop Pass**:
- After Step 7 passes, run `oh-my-codex:ai-slop-cleaner` on **all files changed during the Ralph session**.
- Scope the cleaner to **changed files only**; do not widen the pass beyond Ralph-owned edits.
- Run the cleaner in **standard mode** (not `--review`).
- If the prompt contains `--no-deslop`, skip Step 7.5 entirely and proceed with the most recent successful verification evidence.
7.6 **Regression Re-verification**:
- After the deslop pass, re-run all tests/build/lint and read the output to confirm they still pass.
- If post-deslop regression fails, roll back cleaner changes or fix and retry. Then rerun Step 7.5 and Step 7.6 until the regression is green.
- Do not proceed to completion until post-deslop regression is green (unless `--no-deslop` explicitly skipped the deslop pass).
8. **On approval**: If Codex goal mode is active, call `update_goal({status: "complete"})` before `/cancel`; report final elapsed time and token-budget usage when the tool returns it. Then run `/cancel` to cleanly exit and clean up all state files.
9. **On rejection**: Fix the issues raised, then re-verify with the same `agent_type` and `reasoning_effort` profile
</Steps>
<Tool_Usage>
ask_codex with agent_role: "architect" for verification cross-checks when changes are security-sensitive, architectural, or involve complex multi-system integrationomx state write/read --input '<json>' --json for ralph mode state persistence between iterationsget_goal to discover or re-check the active objective, create_goal only when the user/system explicitly requested a new goal and no active goal exists, and update_goal only after the audited objective is fully achieved.omx_state call reports that its stdio transport is unavailable/closed, do not retry the same MCP call. Retry once through the supported CLI parity surface with the same payload, preserving workingDirectory and session_id: omx state write --input '<json>' --json, omx state read --input '<json>' --json, or omx state clear --input '<json>' --json. If the CLI path also fails, continue with .omx/context / .omx/plans file-backed artifacts and report the state persistence blocker.
</Tool_Usage>Codex goal mode is the thread-level completion contract for long-running Ralph work. Ralph state tracks workflow mechanics; goal mode tracks whether the user objective is truly done. When the goal tools are available:
get_goal during intake or before the first execution loop when the prompt/hook says an active thread goal exists.create_goal only when the user or system explicitly asked for goal tracking; otherwise continue with Ralph state alone.goal.objective as binding acceptance scope. Newer user updates can refine the current branch, but do not silently narrow the goal.$ralplan, $ralph), file, command, test, gate, and deliverable to evidenceupdate_goal({status: "complete"}) only when the audit shows no required work remains. Do not use passing tests, Ralph state, or architect approval as proxy proof unless they cover the whole goal.Use the CLI-first state surface for Ralph lifecycle state (omx state write/read/clear --input '<json>' --json). Explicit MCP compatibility tools (state_write, state_read, state_clear) remain acceptable only when already enabled.
omx state write --input '{"mode":"ralph","active":true,"iteration":1,"max_iterations":10,"current_phase":"executing","started_at":"<now>","state":{"context_snapshot_path":"<snapshot-path>"}}' --jsonomx state write --input '{"mode":"ralph","iteration":<current>,"current_phase":"executing"}' --jsonomx state write --input '{"mode":"ralph","current_phase":"verifying"}' --json or omx state write --input '{"mode":"ralph","current_phase":"fixing"}' --jsonomx state write --input '{"mode":"ralph","active":false,"current_phase":"complete","completed_at":"<now>","completion_audit":{"passed":true,"prompt_to_artifact_checklist":["<requirement mapped to artifact/evidence>"],"verification_evidence":["<fresh test/build/lint command and result>"]}}' --jsonprompt_to_artifact_checklist entries that map every user requirement, workflow gate, named file, command, PR/delivery requirement, and stop condition to a concrete artifact or evidence item.verification_evidence entries with concrete commands, exit status, files inspected, PR URLs, or other machine-checkable evidence.completion_audit field on the Ralph state object. Do not write bare top-level prompt_to_artifact_checklist or verification_evidence fields by themselves; the Stop gate will reject them.omx state read --input '{"mode":"ralph"}' --json and verify completion_audit.passed === true, a non-empty checklist, and non-empty verification evidence before producing the final answer.update_goal({status:"complete"}) only after this Ralph audit read-back succeeds.$cancel (which should call omx state clear --input '{"mode":"ralph"}' --json)Good: The user says continue after the workflow already has a clear next step. Continue the current branch of work instead of restarting or re-asking the same question.
Good: The user changes only the output shape or downstream delivery step (for example make a PR). Preserve earlier non-conflicting workflow constraints and apply the update locally.
Bad: The user says continue, and the workflow restarts discovery or stops before the missing verification/evidence is gathered.
<Examples>
<Good>
Correct parallel delegation:
```
task(agent_type="executor", reasoning_effort="low", prompt="Add type export for UserConfig")
task(agent_type="executor", reasoning_effort="medium", prompt="Implement the caching layer for API responses")
task(agent_type="executor", reasoning_effort="xhigh", prompt="Refactor auth module to support OAuth2 flow")
```
Why good: Three independent tasks fired simultaneously while explicitly selecting the installed `executor` native role, so the UI/tracker does not show default subagents; legacy tier intent is preserved through native reasoning effort (`LOW` -> `low`, `STANDARD` -> `medium`, `THOROUGH` -> `xhigh`).
</Good>
<Good>
Correct verification before completion:
```
1. Run: npm test → Output: "42 passed, 0 failed"
2. Run: npm run build → Output: "Build succeeded"
3. Run: lsp_diagnostics → Output: 0 errors
4. task(agent_type="architect", reasoning_effort="medium", prompt="verify completion") → Verdict: "APPROVED"
5. Run /cancel
```
Why good: Fresh evidence at each step, architect verification, then clean exit.
</Good>
<Bad>
Claiming completion without verification:
"All the changes look good, the implementation should work correctly. Task complete."
Why bad: Uses "should" and "look good" -- no fresh test/build output, no architect verification.
</Bad>
<Bad>
Sequential execution of independent tasks:
```
task(agent_type="executor", reasoning_effort="low", prompt="Add type export") → wait →
task(agent_type="executor", reasoning_effort="medium", prompt="Implement caching") → wait →
task(agent_type="executor", reasoning_effort="xhigh", prompt="Refactor auth")
```
Why bad: These are independent tasks that should run in parallel, not sequentially.
</Bad>
</Examples>
<Escalation_And_Stop_Conditions>
/cancel<Final_Checklist>
task(agent_type="architect", reasoning_effort="medium"...) minimum. On the exact reviewed Codex releases 0.144.5, 0.145.0, 0.146.1, and 0.148.0-alpha.5 when role routing is unavailable, no adapted Ralplan Architect pass is valid; every other version remains unknown and fails closed. When adapted authority is attempted, preflight must have stopped with the leader-proof diagnostic. Ordinary Ralph work remains subject to its existing controls.update_goal({status: "complete"}) was called when an active goal exists/cancel run for clean state cleanup
</Final_Checklist><Advanced>
## PRD Mode (Optional)
When the user provides the --prd flag, initialize a Product Requirements Document before starting the ralph loop.
Check if {{PROMPT}} contains --prd or --PRD.
Prompt-side $ralph workflow activation is lighter-weight than omx ralph --prd ....
It seeds Ralph workflow state and guidance, but it does not implicitly launch the
CLI entrypoint or apply the PRD startup gate. Treat omx ralph --prd ... as the
explicit PRD-gated path.
--no-deslopCheck if {{PROMPT}} contains --no-deslop.
If --no-deslop is present, skip the deslop pass entirely after Step 7 and continue using the latest successful pre-deslop verification evidence.
Ralph execution supports visual reference flags for screenshot tasks:
-i <image-path> (can be used multiple times)--images-dir <directory>Example:
ralph -i refs/hn.png -i refs/hn-item.png --images-dir ./screenshots "match HackerNews layout"
$deep-interview --quick <task>.omx/interviews/{slug}-{timestamp}.md.omx/plans/prd-{slug}.md.omx/state/{scope}/ralph-progress.json (session scope when available, else root scope)--prd flag){
"project": "[Project Name]",
"branchName": "ralph/[feature-name]",
"description": "[Feature description]",
"userStories": [
{
"id": "US-001",
"title": "[Short title]",
"description": "As a [user], I want to [action] so that [benefit].",
"acceptanceCriteria": ["Criterion 1", "Typecheck passes"],
"priority": 1,
"passes": false
}
]
}.omx/state/{scope}/ralph-progress.jsonUser input: --prd build a todo app with React and TypeScript
Workflow: Detect flag, extract task, create .omx/plans/prd-{slug}.md, create .omx/state/{scope}/ralph-progress.json, begin ralph loop.
--prd startup still validates machine-readable story state from .omx/prd.json..omx/plans/prd-{slug}.md remains the canonical storage/documentation artifact, but it is not yet the startup validation source..omx/prd.json exists and canonical PRD is absent, migrate one-way into .omx/plans/prd-{slug}.md..omx/progress.txt exists and canonical progress ledger is absent, import one-way into .omx/state/{scope}/ralph-progress.json.Run in background (run_in_background: true):
Run blocking (foreground):
</Advanced>
Original task: {{PROMPT}}
© 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/ralph of yangyuan-zhen/PolyWeather.
Open the folder on GitHubat commit 43e658b
Ralph 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 |
|---|---|---|---|---|---|---|
| Ralph this skillyangyuan-zhen/PolyWeather | 316 | — | ~5.7k | Automated safety check: Pass | AGPL-3.0 | |
| RalphYeachan-Heo/oh-my-claudecode | 40k | — | ~7.5k | Automated safety check: Pass | MIT | |
| Agent Repo Architectruvnet/ruflo | 74k | 2 repos | ~3k | Automated safety check: Pass | MIT | |
| Hindsight Architectvectorize-io/hindsight | 48k | — | ~10k | Automated safety check: Notes | MIT | |
| Ralphzereight/gitlab-mcp | 2k | 1 repos | ~711 | Automated safety check: Pass | MIT | |
| Ralph Loopcursor/plugins | 11k | — | ~469 | Automated safety check: Pass | None |
Yeachan-Heo/oh-my-claudecode
Self-referential loop until task completion with configurable verification reviewer
ruvnet/ruflo
Agent skill for repo-architect - invoke with $agent-repo-architect
vectorize-io/hindsight
Expert memory architect. An agent skill from vectorize-io/hindsight.
zereight/gitlab-mcp
PRD-driven persistence loop until task completion with verification.
cursor/plugins
Start a Ralph Loop for iterative self-referential development.
ruvnet/ruflo
Agent skill for v3-integration-architect - invoke with $agent-v3-integration-architect
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
[OMX] Self-referential loop until task completion with architect verification. Ralph is an agent skill from yangyuan-zhen/PolyWeather.
Run `npx skills add yangyuan-zhen/PolyWeather --skill ralph -a claude-code`. Or copy the skill folder (.codex/skills/ralph in yangyuan-zhen/PolyWeather) into .claude/skills/ralph in your project. Claude Code loads it when a task matches its description.
Run `npx skills add yangyuan-zhen/PolyWeather --skill ralph -a codex`. Or copy the skill folder (.codex/skills/ralph in yangyuan-zhen/PolyWeather) into .agents/skills/ralph 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 ralph -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ralph, .gemini/skills/ralph, .github/skills/ralph and .opencode/skills/ralph in your project.
Going by SKILL.md and its folder, Ralph needs the command-line tools its instructions call (make).
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.
Ralph 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 5.7k 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 Ralph: Ralph (Yeachan-Heo/oh-my-claudecode, 40k stars), Agent Repo Architect (ruvnet/ruflo, 74k stars), Hindsight Architect (vectorize-io/hindsight, 48k stars) and Ralph (zereight/gitlab-mcp, 2k 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.