ULW Loop
code-yeongyu/oh-my-openagent
Runs a long task as a checkpointed goal loop: it creates goals, mirrors each step into a todo list, gathers evidence per criterion and lands every goal before the next.
Runs a light task loop where each goal criterion passes only when a real evidence artifact exists, with progress stored in a `.superloopy` folder.
$ npx skills add beefiker/superloopy --skill superloopy-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install beefiker/superloopy superloopy-loop --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/beefiker/superloopy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/superloopy-loop .claude/skills/superloopy-loop && 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 "superloopy-loop" agent skill from https://github.com/beefiker/superloopy/tree/main/skills/superloopy-loop into .claude/skills/superloopy-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "superloopy-loop", 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/beefiker/superloopy/tree/main/skills/superloopy-loopType 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 beefiker/superloopy --skill superloopy-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install beefiker/superloopy superloopy-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/beefiker/superloopy.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/superloopy-loop .agents/skills/superloopy-loop && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "superloopy-loop" agent skill from https://github.com/beefiker/superloopy/tree/main/skills/superloopy-loop into .agents/skills/superloopy-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "superloopy-loop", 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 beefiker/superloopy --skill superloopy-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install beefiker/superloopy superloopy-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/beefiker/superloopy.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/superloopy-loop .cursor/skills/superloopy-loop && 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 "superloopy-loop" agent skill from https://github.com/beefiker/superloopy/tree/main/skills/superloopy-loop into .cursor/skills/superloopy-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "superloopy-loop", 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/beefiker/superloopy.git --path skills/superloopy-loop--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 beefiker/superloopy --skill superloopy-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install beefiker/superloopy superloopy-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/beefiker/superloopy.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/superloopy-loop .gemini/skills/superloopy-loop && 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 "superloopy-loop" agent skill from https://github.com/beefiker/superloopy/tree/main/skills/superloopy-loop into .gemini/skills/superloopy-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "superloopy-loop", 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 beefiker/superloopy superloopy-loopInstalls 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 beefiker/superloopy --skill superloopy-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/beefiker/superloopy.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/superloopy-loop .github/skills/superloopy-loop && 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 "superloopy-loop" agent skill from https://github.com/beefiker/superloopy/tree/main/skills/superloopy-loop into .github/skills/superloopy-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "superloopy-loop", 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 beefiker/superloopy --skill superloopy-loop -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install beefiker/superloopy superloopy-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/beefiker/superloopy.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/superloopy-loop .opencode/skills/superloopy-loop && 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 "superloopy-loop" agent skill from https://github.com/beefiker/superloopy/tree/main/skills/superloopy-loop into .opencode/skills/superloopy-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "superloopy-loop", 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.
superloopy-loopRuns a light task loop where each goal criterion passes only when a real evidence artifact exists, with progress stored in a `.superloopy` folder.
Superloopy keeps durable state in `.superloopy/`, or in a per-session subfolder, and the agent changes it only through the `superloopy` CLI, never by editing `goals.json` by hand. A criterion can pass only after an artifact exists under the active evidence root, and tests count as useful evidence but do not finish the task alone. Executor receipts end with a line naming the evidence path.
Opening a message with `loopy` makes the agent the loop engineer: it runs `superloopy loop begin`, follows `loop guide` for each step, proves criteria with `loop prove`, preflights with `loop check` and closes with `loop finish`. Lighter triggers such as `loopywork` and `lpy` only inject guidance. User steering uses a `SUPERLOOPY_STEER` JSON message, and the skill bundles an OpenAI agent config, a reference on reassurance copy and a script that audits it.
Read from SKILL.md and the folder at commit 4bb19dd. 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.
Ships 1 file in scripts/ (JavaScript), which the agent can run.
Shell commands in SKILL.md call:
gitnodeFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
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.
Superloopy Evidence Loop loads about 5.9k tokens when it runs, and up to ~6.4k if it reads all its reference files. Until then it costs about 38 tokens; SKILL.md has 2,970 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); the scripts in this folder are not scanned.
The full file from beefiker/superloopy at commit 4bb19dd, republished under its MIT licence (© beefiker). 2,970 words, ~5,921 tokens.
.claude/skills/superloopy-loop/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Use this skill when the user asks for Superloopy, loopywork, lpy, a loop harness, durable criteria, evidence-backed completion, strict-but-light task flow, or guided next actions.
.superloopy/, or .superloopy/sessions/<id>/ when --session-id is used..superloopy/goals.json; use the CLI.SUPERLOOPY_STEER JSON; do not hand-edit .superloopy/goals.json.SUPERLOOPY_EVIDENCE: <path-under-active-evidence-root>.EVIDENCE_RECORDED receipts remain accepted for compatibility.superloopy loop prove when an active goal needs command-backed evidence for its next unresolved criterion.loopy keyword wakes the loop engineer: take the rest of the prompt as the brief, run the loop yourself, and report progress instead of asking the user to type Superloopy commands.loopywork, $lpy, and lpy are lighter prompt triggers; they inject guidance but never mutate .superloopy/ state by themselves.say-it-straight off / 직설 모드 끄기 and say-it-straight on / 직설 모드 켜기 controls apply only to the current incomplete loop; new loops reset this default to enabled.i-have-adhd still owns structure, and humanize-korean still owns Korean artifact rewriting.loopy keyword)When the user opens a message with loopy <task>, act as the loop engineer:
superloopy loop begin --brief "<task>" --mode light --json; do not create a second plan if one is active.superloopy loop guide --json, prove criteria with superloopy loop prove -- <command>, preflight with superloopy loop check, then finish with superloopy loop finish --evidence "<summary>" --artifact .superloopy/evidence/gate.json --json.loopy <task>. You run every Superloopy command and report progress as criteria proven and the next step.loopy with no task asks what to build; loopy mid-loop resumes from existing state. The Stop hook is packaged with the plugin but stays inert until SUPERLOOPY_STOP_HOOK=on; when enabled, it blocks completion until evidence exists.humanize-korean semantic review for misplaced modifiers.Read the detailed reassurance-copy reference when this condition applies. Artifact ownership decides the condition; prompt wording does not.
loopy team)The loop engineer directive is injected for every loopy prompt, and it scales to the work:
loopy <task> drives one agent through the loop. The directive still permits light delegation: if the work splits into 2+ genuinely independent slices, you may fan them out with the native subagent controls exposed by the current host; keep each assignment self-contained. For a single cohesive change, stay solo.loopy team <task> / loopy crew <task>, the connected one-word loopycrew <task>, or the standalone ultrawork <task>). The same engineer escalates into full fan-out: dispatch the crew across independent lanes, collect them with the host's native lifecycle controls, and record only artifact-backed proof. The escalation keyword is stripped from the brief that seeds the loop. This is the active counterpart to "Optional Subagent-Driven Mode" below — same dispatch contract, receipt gate, and mandatory handoff/fleet tracking.Each crew dispatch uses the configured name when the host exposes named selection: franky to build, zoro to review, usopp to test, jinbe to gate, robin to audit, and nami to navigate. The assignment also stays self-contained (TASK: act as <role> ...). The orchestrator itself runs on the model the user selected in the host (gpt-6-astra is allowed when selected); crew lanes keep their model-policy.json pins and never inherit the orchestrator's model. The host-owned stop callback observes the actual role identity; if the host cannot attest that identity or model, report role_unverified or model_unverified.
Both tiers are steering, not enforcement: the directive instructs the main agent, and actual spawning depends on the host's native multi-agent tool being available. Superloopy never spawns; it gates the evidence workers deliver. See "Optional Subagent-Driven Mode" for the full dispatch contract and crew roles.
The optional Stop hook is a bounded, progress-gated engine, not a one-shot nudge. With SUPERLOOPY_STOP_HOOK=on, while work remains it keeps driving you toward evidence-backed completion, counting iterations in .superloopy/loop-control.json.
superloopy loop check + superloopy loop finish with real artifacts.blocked (visible in superloopy loop status) and asks for a human — it never fabricates a done.blocked: when the host transcript shows a usage/rate/quota-limit marker, the loop is marked paused (reason quota) in .superloopy/loop-control.json — a resumable state. It does not burn the no-progress counter and is never mistaken for completion; a loop_paused/loop_resumed pair is written to the ledger. Superloopy is hook-driven and cannot self-wake, so it only pauses cleanly and stays resumable — see "Auto-resume after a quota reset" below.SUPERLOOPY_MAX_ITERATIONS (default 50, 0 = unlimited; the no-progress guard stays active), SUPERLOOPY_MAX_STALLED (default 3), SUPERLOOPY_CONTINUATION=off (legacy single continuation), SUPERLOOPY_QUOTA_MARKERS (comma/newline list of extra host-specific limit phrases — the built-in set is conservative, so set this to your host's exact banner text).Superloopy detects the limit and pauses; waking when quota resets is an external job (Superloopy has no daemon). Run an idempotent scheduler that resumes the loop and stops once it is done:
superloopy loop status --json: if summary.aggregateComplete is false, resume by re-running the loop (loopy <continue>, or superloopy loop guide --json then the next command); if complete, no-op.superloopy loop audit independently re-checks recorded proof. Superloopy itself re-runs each command-backed passed criterion (the deterministic source of truth) and records the result in .superloopy/audit-state.json; a re-run that does not reproduce is marked inconclusive, never a silent fail.
robin subagent: it judges the re-run against the scenario and ends with SUPERLOOPY_AUDIT: <verdict-path>. When the receipt arrives, Superloopy re-derives that criterion's floor in-process (it does not trust the recorded .superloopy/audit-state.json, which the worker can write) and accepts the verdict only if it is hash-bound to that fresh re-run. Floor dominance is symmetric: the verdict may act only when the re-run reproduces — it can neither upgrade nor flip a non-reproducing (inconclusive) re-run.superloopy loop review/checkpoint re-derive every passed criterion (not just the cited ones) and hash-verify every cited audit verdict, so a regressed command criterion can't be skipped and a structurally valid audit section pointing at hand-written verdict files cannot authorize completion.superloopy loop prove -- <command>) wherever the work allows — the autonomous loop engineer does this by default, so most criteria get the strong guarantee automatically.verdict: fail) flips the criterion off pass with the gap recorded in its notes, so the continuation engine re-drives exactly that criterion to be fixed and re-audited. A non-reproducing command re-run is inconclusive and never auto-flips (flaky-test safety).SUPERLOOPY_AUDIT_MAX_FAILS (default 3) audit failures on the same criterion, it is marked blocked for a human instead of looping. Accepted audits are counted monotonically so honest fix → re-audit cycles register as progress..superloopy/audit-state.json and .superloopy/loop-control.json are worker-writable, so the deterministic floor is re-derived in-process at both verdict acceptance and the completion gate — a forged state file cannot manufacture an accepted pass. The continuation counters (auditsAccepted, stall/high-water) are runaway backstops, not a security boundary; completion authority stays the plan's, and the engine never force-completes.Use project custom agents from .codex/agents/ only when the user asks for subagents or the work has independent implementation, review, and QA lanes. The normal single-agent Superloopy flow remains the default for small changes.
Superloopy provisions and tracks these agents; the host (Codex) spawns them. Superloopy never spawns. The host spawn surface cannot reliably select a bundled TOML role, model, or reasoning effort by name, so every dispatch must be self-contained and judged by delivered evidence — never by the role label requested. See docs/superloopy-host-contract.md.
Plugin installs bootstrap the superloopy command wrapper and bundled custom agents on the first approved SessionStart hook. If the host does not run that hook, run node src/cli.js install --json from the Superloopy checkout or installed plugin root. superloopy agents install remains available to copy only the bundled custom agents into the personal Codex agents directory ($CODEX_HOME/agents when set, otherwise ~/.codex/agents). Restart Codex after installation.
Parent agent responsibilities:
cwd, verify and state the exact target path before editing or dispatching workers.superloopy loop prove, superloopy loop evidence, superloopy loop review, or superloopy loop checkpoint.superloopy loop handoff --agent <name> --assignment <text> [--verdict <v>] [--artifact <path>] and run superloopy loop fleet --json before the final gate. The fleet output normalizes the workers' APPROVE/PASS/REJECT-style verdicts into one accept/reject/needs-context enum and lists outstanding workers. An accepted verdict requires a valid artifact under the active evidence root. A lifecycle verdict (working/in_progress/running) stays outstanding; an unresolved verdict (inconclusive/timeout/ack_only) normalizes to needs-context and is NEVER counted as accept. Rejected and needs-context lanes appear in attention. Known crew lanes may print one original completion line for terminal verdicts, choosing the user's language from the assignment or scoped brief when it matches the supported catalog (en, ko, ja, zh, es, fr, de, it, pt, id, hi, tr, vi, ru, ar, th), but the line is presentation only; artifacts, normalized verdicts, attention, and outstanding remain authoritative. Use --language <tag> or SUPERLOOPY_CREW_LANGUAGE=<tag> only when the prompt language cannot be inferred. Set SUPERLOOPY_MAX_PARALLEL for a soft over-dispatch warning. Handoffs are parent-side bookkeeping only — they never spawn or complete.git status --short --untracked-files=all and git ls-files --others --exclude-standard so new evidence, scripts, and reports are not omitted from the diff review.Because role-by-name routing is unverified, each spawn message must stand alone — paste the role's requirements into it rather than relying on the agent name. Lead with an imperative TASK: and name the rest:
TASK: the one bounded assignment (one criterion or one non-overlapping slice).DELIVERABLE: the report artifact path under the active evidence root, and the required receipt (SUPERLOOPY_EVIDENCE for workers; SUPERLOOPY_AUDIT for robin; nami writes none).SCOPE: allowed files, the active evidence root, the validation command, and explicit non-goals.VERIFY: the binary check that decides PASS/FAIL.State that it is an executable assignment, not a context handoff. Prefer a fresh, minimal context over a full-history fork so the child works the delegated task instead of continuing old parent state.
WORKING: <task> - <phase>; reserve BLOCKED: <reason> for genuine stalls.Agent allocation:
franky: edits one criterion or independent slice, writes a report, and ends with SUPERLOOPY_EVIDENCE: <path-under-active-evidence-root>.zoro: reviews diff, scope, and evidence; writes a report under the active evidence root; does not edit product files.usopp: exercises happy-path, regression, and risk scenarios; writes artifact-backed QA evidence; does not edit product files.jinbe: integrates implementation, review, QA, audit, and criteria coverage; writes a final gate report such as .superloopy/evidence/jinbe-final-gate-report.md; the parent still runs Superloopy completion commands.robin: read-only, skeptical evidence auditor; judges Superloopy's deterministic re-run against the scenario and ends with SUPERLOOPY_AUDIT: <verdict-path>. Installed by superloopy agents install alongside the workers.nami: read-only codebase navigator; locates files and code and returns absolute paths with a direct answer. Writes no evidence and edits nothing — dispatch it first to scope a slice before assigning an executor. Parallelize it with review/QA lanes.superloopy loop begin --brief "<task>" --mode light --json
superloopy loop create --brief "<task>" --mode light --json
superloopy loop create --brief "<task>" --session-id "<id>" --mode strict --json
superloopy loop create --brief $'@goal: Build\n<story one>\n@goal: Verify\n<story two>' --json
superloopy loop guide --json
superloopy loop trace
superloopy loop report
superloopy loop check
superloopy doctor --comparison-path /path/to/comparison --jsonstatus is the fastest reorientation command; it returns current counts and the immediate guide.
create returns the immediate guide too; follow it with next unless you used begin.
begin already starts the first goal and returns the immediate guide, including the next proof command.
The guide shows the next command, proof target, recorded evidence, proof plan, capture template, and evidence template. It also shows recorded evidence for already-passed criteria with each captured timestamp, a flow checklist for start or resume, record artifact-backed proof, check evidence, and finish with quality gate, unresolved criteria with suggested proof paths, manual evidence templates, plus the trace, report, and check commands for evidence inspection. Capture, evidence, and repair templates include --notes "<summary>" so proof rows stay self-documenting.
For the active goal's next unresolved criterion, prove command-backed evidence directly:
superloopy loop prove -- npm testFor explicit criterion targeting, write artifacts under .superloopy/evidence/ or capture a command transcript:
superloopy loop capture --goal-id G001 --criterion-id C001 -- npm test
superloopy loop evidence --goal-id G001 --criterion-id C001 --status pass --artifact .superloopy/evidence/<artifact>.txt --notes "<summary>" --jsonInspect the evidence trail when reporting progress or looking for missing proof:
superloopy loop trace
superloopy loop reporttrace and report both return the next guide action after showing or writing evidence context, including evidence summary counts and a timestamped timeline from the ledger. Their artifact rows include capture times for already-recorded proof, and timeline rows include manual evidence notes when provided. The report artifact also includes recorded evidence with captured timestamp, an Evidence Summary section, the current next action, proof plan, and suggested artifact paths for criteria still missing proof.
Run the lightweight preflight before finishing:
superloopy loop checkcheck prints an evidence summary with artifact-backed criteria, unresolved, and invalid counts. If it is blocked, use the numbered repair plan: each step names the target artifact, capture command, and manual evidence alternative.
trace, check, and report also surface warnings for commandless manual proof and exhausted worker/auditor attempts. Warnings do not fail a preflight by themselves, but they are a prompt to prefer command-backed proof or close an inconclusive lane.
Finish in one command after all criteria pass:
superloopy loop finish --evidence "<summary>" --artifact .superloopy/evidence/gate.json --jsonKeep the human final gate report and the Superloopy quality gate artifact separate. A jinbe report is Markdown evidence (for example .superloopy/evidence/jinbe-final-gate-report.md). The superloopy loop review and superloopy loop finish --artifact flag writes the machine-validated quality gate artifact and must point to JSON, normally .superloopy/evidence/gate.json. Never pass the Markdown report path as the finish artifact.
For custom gate workflows:
superloopy loop review --status passed --artifact .superloopy/evidence/gate.json --notes "<summary>" --json
superloopy loop checkpoint --goal-id G001 --status complete --evidence "<summary>" --quality-gate .superloopy/evidence/gate.json --jsonWhen a final proof command can be satisfied from cache but the task needs fresh evidence, capture a rerun variant in the artifact, for example Gradle --rerun-tasks on the focused JVM test. Use this for final evidence capture, not as a default tax on every local check.
Every listed artifact must exist, be non-empty, and live under the active evidence root. Superloopy also accepts strict review gates and matrix gates when reviewer/architect, executor QA, rerun, artifact, and coverage fields validate.
For executor receipts, use the active evidence root. A global loop normally records under .superloopy/evidence/; a scoped loop records under .superloopy/sessions/<id>/evidence/. If a receipt is missing or invalid, the receipt block message names the active evidence root to repair.
Accept only structured prompt-level steering:
SUPERLOOPY_STEER: {"kind":"annotate","evidence":"fact","rationale":"why it matters"}
SUPERLOOPY_STEER: {"kind":"add_goal","title":"New slice","objective":"Concrete objective","rationale":"why it changed"}
SUPERLOOPY_STEER: {"kind":"revise_criterion","goalId":"G001","criterionId":"C002","scenario":"New scenario.","rationale":"why it changed"}
SUPERLOOPY_STEER: {"kind":"reorder_pending","goalIds":["G003","G002"],"rationale":"why this order"}After any accepted steering, follow the returned guide; run superloopy loop status --json when you need a fresh reorientation.
superloopy doctor --json checks the package, hooks, bundled skills, CLI, dependency-free boundary, runtime ignore policy, file inventory, gate notes, design audit, generic comparison scan status, dispatch coherence, model policy, and reviewability.
Use superloopy doctor --comparison-path /path/to/comparison --json only when you need copied-block evidence against an external folder. The generic comparison scan compares code-shaped files for substantial contiguous blocks without naming or coupling Superloopy to any source project.
© beefiker, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts, references) in skills/superloopy-loop of beefiker/superloopy.
Open the folder on GitHubat commit 4bb19dd
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in beefiker/superloopy, which our catalogue first saw on October 7, 2026.
Superloopy Evidence Loop 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 |
|---|---|---|---|---|---|---|
| Superloopy Evidence Loop this skillbeefiker/superloopy | 111 | 1 repos | ~5.9k | Automated safety check: Pass | MIT | |
| ULW Loopcode-yeongyu/oh-my-openagent | 70k | — | ~3.2k | Automated safety check: Pass | Custom licence | |
| Show Me Your Work Decision Logcursor/plugins | 10k | 9 repos | ~1.6k | Automated safety check: Pass | None | |
| Incremental Implementationaddyosmani/agent-skills | 102k | 1 repos | ~2.3k | Automated safety check: Pass | MIT | |
| PUA Looptanweai/pua | 20k | — | ~1.1k | Automated safety check: Pass | MIT | |
| agtx One-Shot Project Runnerfynnfluegge/agtx | 1.7k | — | ~3.8k | Automated safety check: Pass | Apache-2.0 |
code-yeongyu/oh-my-openagent
Runs a long task as a checkpointed goal loop: it creates goals, mirrors each step into a todo list, gathers evidence per criterion and lands every goal before the next.
cursor/plugins
Keeps a TSV decision log for long or unattended agent runs, one row per decision with what, why, evidence and result, so a reviewer can check the work later.
addyosmani/agent-skills
Delivers a change in thin vertical slices, each implemented, tested, verified and committed before the next, using vertical, contract-first or risk-first slicing.
tanweai/pua
Runs an unattended iterate-until-verified loop in which a user-set verify command, not the agent's own claim, decides when the task is finished.
fynnfluegge/agtx
Runs a whole project unattended on an agtx kanban board, decomposing the goal, starting tasks, unblocking workers and merging each result.
cursor/plugins
Splits a large goal into a tree of parallel Cursor cloud agents, with planners, workers and verifiers coordinated by a script and reporting through structured handoffs.
beefiker/superloopy
Rewrites already-written Korean text to remove AI-sounding rhythm and translationese while keeping its meaning, register, facts and protected terms untouched.
beefiker/superloopy
Routes backend work in the Superloopy loop harness to the right reference module, covering API contracts, schema migrations, transactions, background jobs, caching and security.
beefiker/superloopy
Creates zero-dependency, animation-rich HTML slide decks that run in the browser, with style presets, PowerPoint conversion and PDF export, proven by a real-browser render.
beefiker/superloopy
A read-only health check for a Superloopy install or checkout: state folders, evidence files, bundled agents, hooks, wrapper and plugin registration, reported before any repair.
beefiker/superloopy
Reshapes the agent's replies for an ADHD-friendly reading style: the next action first, numbered single-action steps, visible progress and one concrete action at the end.
beefiker/superloopy
Use only after explicit Codex $superloopy:say-it-straight or Claude Code /superloopy:say-it-straight invocation to make supplied or requested prose direct, concise, and natural without changing…
Categories
Runs a light task loop where each goal criterion passes only when a real evidence artifact exists, with progress stored in a `.superloopy` folder. json` by hand. A criterion can pass only after an artifact exists under the active evidence root, and tests count as useful evidence but do not finish the task alone.
Superloopy Evidence Loop fits situations like: tasks that need criteria tracked across a long session and finished with proof; you want completion backed by artifacts, not by the agent's own claim; steering an in-progress loop with a change of goal or priority.
Run `npx skills add beefiker/superloopy --skill superloopy-loop -a claude-code`. Or copy the skill folder (skills/superloopy-loop in beefiker/superloopy) into .claude/skills/superloopy-loop in your project. Claude Code loads it when a task matches its description.
Run `npx skills add beefiker/superloopy --skill superloopy-loop -a codex`. Or copy the skill folder (skills/superloopy-loop in beefiker/superloopy) into .agents/skills/superloopy-loop 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 beefiker/superloopy --skill superloopy-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/superloopy-loop, .gemini/skills/superloopy-loop, .github/skills/superloopy-loop and .opencode/skills/superloopy-loop in your project.
Going by SKILL.md and its folder, Superloopy Evidence Loop needs JavaScript for the scripts in its folder and the command-line tools its instructions call (git and node). Our summary lists: The `superloopy` CLI.
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Superloopy Evidence Loop is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.9k tokens (SKILL.md is roughly 24k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 505 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Superloopy Evidence Loop: ULW Loop (code-yeongyu/oh-my-openagent, 70k stars), Show Me Your Work Decision Log (cursor/plugins, 10k stars), Incremental Implementation (addyosmani/agent-skills, 102k stars) and PUA Loop (tanweai/pua, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
beefiker (a GitHub user) maintains it in beefiker/superloopy, which has 111 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 6, 2026.
Source: beefiker/superloopy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.