Agent skill

Superloopy Evidence Loop

by beefiker in beefiker/superloopy

Runs a light task loop where each goal criterion passes only when a real evidence artifact exists, with progress stored in a `.superloopy` folder.

MITAuto-check passedAgent Workflows

Install Superloopy Evidence Loop

skills CLI
$ npx skills add beefiker/superloopy --skill superloopy-loop -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install beefiker/superloopy superloopy-loop --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
superloopy-loop
GitHub stars
111
Used in
1 other repo
Token cost
~5.9k tokens
SKILL.md length
2,970 words
Files
4 (incl. scripts, references)
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Runs a light task loop where each goal criterion passes only when a real evidence artifact exists, with progress stored in a `.superloopy` folder.

  • Tasks that need criteria tracked across a long session and finished with proof
  • SKILL.md covers Contract, Loop engineer (loopy keyword), Continuation Engine and Evidence Audit, plus 5 more sections
  • Runs JavaScript scripts from its folder; calls git and node
  • You want completion backed by artifacts, not by the agent's own claim

What it does

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.

When your agent uses it

  • 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

Example prompts

  • “loopy migrate the settings page to the new form component and prove each step.”
  • “Start a Superloopy run for the API cleanup and show me the next guided action.”
  • “Use lpy to check which criteria in the current goal still lack evidence.”

Requirements

  • The `superloopy` CLI

What it can do on your machine

Read from SKILL.md and the folder at commit 4bb19dd. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 1 file in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • git
    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    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.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~38
When it runs · the whole SKILL.md, loaded when a task matches
~5.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.4k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from beefiker/superloopy at commit 4bb19dd, republished under its MIT licence (© beefiker). 2,970 words, ~5,921 tokens.

Download SKILL.mdSave it as .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.
name
superloopy-loop
description
Use Superloopy's lightweight strict-evidence loop for Codex tasks that need durable progress, criteria, and artifact-backed completion.
metadata.short-description
Lightweight strict-evidence loop harness

superloopy-loop

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.

Contract

  • State lives in .superloopy/, or .superloopy/sessions/<id>/ when --session-id is used.
  • Do not hand-edit .superloopy/goals.json; use the CLI.
  • A criterion can pass only after a real artifact exists under the active evidence root.
  • User steering must use SUPERLOOPY_STEER JSON; do not hand-edit .superloopy/goals.json.
  • Executor receipts should end with SUPERLOOPY_EVIDENCE: <path-under-active-evidence-root>.
  • Legacy EVIDENCE_RECORDED receipts remain accepted for compatibility.
  • Tests are useful evidence, but completion requires the Superloopy evidence artifact.
  • Use superloopy loop prove when an active goal needs command-backed evidence for its next unresolved criterion.
  • Keep the workflow lightweight unless the task genuinely needs heavier review.
  • A leading 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.
  • Full Loopy runs default to direct, concise, complete user-facing progress and final responses. Exact 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.
  • This output overlay changes wording only. It never silently rewrites supplied prose, task artifacts, code, documentation, comments, evidence, quotations, or user source text; direct artifact editing remains explicit-only. i-have-adhd still owns structure, and humanize-korean still owns Korean artifact rewriting.

Loop engineer (loopy keyword)

When the user opens a message with loopy <task>, act as the loop engineer:

  • Start once with superloopy loop begin --brief "<task>" --mode light --json; do not create a second plan if one is active.
  • Drive each step from 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.
  • The user types only 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.
Reassurance-copy gate (conditional)
  • Decide from the affected artifact: if it creates or changes user-visible Korean product copy about behavior, add a plan criterion for RC-1 through RC-4 and Korean naturalness.
  • State supplied outcomes, fallback, recovery, or next action; preserve verified privacy/legal commitments; never invent behavior.
  • Apply humanize-korean semantic review for misplaced modifiers.
  • Ignore internal logs, developer docs, quotations, general/marketing prose, and non-Korean copy.

Read the detailed reassurance-copy reference when this condition applies. Artifact ownership decides the condition; prompt wording does not.

Two tiers: solo and crew (loopy team)

The loop engineer directive is injected for every loopy prompt, and it scales to the work:

  • Solo (default). A plain 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.
  • Crew (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.

Continuation Engine

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.

  • Progress is measured by recorded proof (passed criteria and completed goals) against a high-water mark; only new proof resets the no-progress counter.
  • It never completes anything. Completion stays the plan's authority via superloopy loop check + superloopy loop finish with real artifacts.
  • A cap or no-progress stall marks the loop blocked (visible in superloopy loop status) and asks for a human — it never fabricates a done.
  • Quota/usage limits are distinct from 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.
  • Knobs: 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).
Auto-resume after a quota reset

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:

  • Read 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.
  • Schedule it on a cadence that outlasts the limit window — a host cron / cloud routine every 20–30 min, or aligned to a known weekly reset. The first run after the reset succeeds; earlier runs simply no-op while still limited.
  • Keep it idempotent and self-terminating, exactly like Superloopy's own gates. Superloopy supplies the resumable state; the scheduler supplies the wake.

Evidence Audit

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.

  • For independent judgment, dispatch a read-only 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.
  • At completion the deterministic spine actually gates the result: 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.
  • Command-backed vs manual proof: the deterministic guarantee is strongest for command-backed criteria — Superloopy re-runs the command and reads the live exit code. A manual (commandless) criterion can only be re-validated for artifact existence; its correctness is not command-reproducible and rests on the auditor's (autonomous LLM) judgment and human review, not on the deterministic floor. Prefer command-backed proof (superloopy loop prove -- <command>) wherever the work allows — the autonomous loop engineer does this by default, so most criteria get the strong guarantee automatically.
  • A failed audit (deterministic floor fail or a 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).
  • After 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.
  • Honest limit: Superloopy cannot verify the auditor subagent was spawned isolated/read-only — it trusts the host's agent frame for that. It does NOT, however, trust its own recorded state: .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.

Optional Subagent-Driven Mode

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:

  • Keep the Superloopy plan and criteria as the source of truth.
  • If the requested repository path differs from cwd, verify and state the exact target path before editing or dispatching workers.
  • Allocate one bounded handoff card per worker: goal, criterion or slice, allowed files, active evidence root, report artifact target, validation command, non-goals, and expected status values.
  • Avoid parallel executors on overlapping files. Parallelize read-heavy review, QA, and summarization lanes first.
  • In full crew mode, the implementation worker must own a real bounded implementation slice before the parent edits or completes that slice. If there is no safe independent implementation slice, stay solo or use a smaller read-only crew instead of pretending an implementer lane ran.
  • Wait for worker summaries, then record only artifact-backed proof with superloopy loop prove, superloopy loop evidence, superloopy loop review, or superloopy loop checkpoint.
  • Summarize worker output by status, claim, changed files, commands, artifacts, risks, and next action. Do not paste raw transcripts into the main thread unless they are the evidence.
  • After each worker finishes, show the user a concise role completion line with the role, normalized verdict, artifact path, and next action before closing or respawning that lane.
  • For full crew, record each dispatch with 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.
  • Before the final summary, run untracked-aware status commands such as 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.
Show full SKILL.md (938 more words)Show less
Dispatch contract (self-contained)

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.

Subagent lifecycle
  • Treat a running child as alive, not as a timeout counter. For a long pass, have it emit WORKING: <task> - <phase>; reserve BLOCKED: <reason> for genuine stalls.
  • Do not record a criterion pass, mark a dependent step done, or finish the loop while a live child still owns that step's evidence.
  • A silent or ack-only child after follow-up is inconclusive — never an approval or a pass. Close the lane, record it as inconclusive, and respawn a smaller self-contained task with only the missing deliverable.

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.

Basic Flow

sh
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 --json

status 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:

sh
superloopy loop prove -- npm test

For explicit criterion targeting, write artifacts under .superloopy/evidence/ or capture a command transcript:

sh
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>" --json

Inspect the evidence trail when reporting progress or looking for missing proof:

sh
superloopy loop trace
superloopy loop report

trace 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:

sh
superloopy loop check

check 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:

sh
superloopy loop finish --evidence "<summary>" --artifact .superloopy/evidence/gate.json --json

Keep 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:

sh
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 --json

When 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.

Quality Gate

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.

Steering

Accept only structured prompt-level steering:

text
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.

Doctor

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

Files

SKILL.md and 3 other files (scripts, references) in skills/superloopy-loop of beefiker/superloopy.

  • SKILL.md
  • agents/openai.yaml
  • references/reassurance-copy.md
  • scripts/audit-reassurance-copy.mjs

Open the folder on GitHubat commit 4bb19dd

Used in 1 other repository

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.

Compare with similar skills

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  • Humanize Korean Prose

    beefiker/superloopy

    Rewrites already-written Korean text to remove AI-sounding rhythm and translationese while keeping its meaning, register, facts and protected terms untouched.

    111 GitHub starsUsed in 1 repo~1.7k tokens
    Auto-check passed
  • Superloopy Backend Routing

    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.

    111 GitHub starsUsed in 1 repo~3k tokens
    Auto-check passed
  • Superloopy Slides

    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.

    111 GitHub starsUsed in 1 repo~8.8k tokens
    Auto-check passed
  • Superloopy Doctor

    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.

    111 GitHub starsUsed in 1 repo~1.9k tokens
    Auto-check passed
  • ADHD-Friendly Output Style

    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.

    111 GitHub starsUsed in 1 repo~1.8k tokens
    Auto-check passed
  • Say It Straight

    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…

    111 GitHub starsUsed in 1 repo~1.3k tokens
    Auto-check passed

Categories

Questions about Superloopy Evidence Loop

What does Superloopy Evidence Loop do?

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.

When should I use Superloopy Evidence Loop?

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.

How do I install Superloopy Evidence Loop in Claude Code?

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.

How do I install Superloopy Evidence Loop in Codex?

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.

Can I use Superloopy Evidence Loop in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Superloopy Evidence Loop need to run?

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.

Does Superloopy Evidence Loop access the network?

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.

Is Superloopy Evidence Loop safe to install?

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.

What licence does Superloopy Evidence Loop use?

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.

How many tokens does Superloopy Evidence Loop use?

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.

What are the alternatives to Superloopy Evidence Loop?

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.

Who maintains Superloopy Evidence Loop?

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.