Autonomous iteration loop: modify, verify, keep/discard against any metric
npx skills add https://github.com/mxyhi/ok-skills --skill autoresearch
Iterations: unlimited.autoresearch/{subcommand}-{YYMMDD}-{HHMM}/ directory.handoff.json. Evals reads *-results.tsv.$autoresearch)Parse the invocation in this order:
| Condition | Mode |
|---|---|
| Metric: or Verify: present | Classic — existing metric loop, unchanged |
| Free-form natural-language goal, no metric/verify | Orchestrator — see Orchestrator section |
| Nothing | Setup wizard — interactive config builder |
| --classic flag | Force Classic regardless of goal text |
| --auto flag | Force Orchestrator regardless of goal text |
Print a banner on every invocation: [autoresearch] mode: classic | orchestrator | wizard.
| Command | Does | Default Iterations |
|---|---|---|
| $autoresearch | Iterate against a metric: modify → verify → keep/discard | 25 |
| $autoresearch plan | Convert a goal into validated Scope, Metric, Verify config | N/A |
| $autoresearch debug | Hunt bugs: hypothesize → test → falsify → repeat | 15 |
| $autoresearch fix | Crush errors one-by-one until zero remain | 20 |
| $autoresearch security | STRIDE + OWASP audit with red-team personas | 15 |
| $autoresearch ship | Ship through 8 phases: checklist → dry-run → deploy → verify | N/A |
| $autoresearch scenario | Generate edge cases across 12 dimensions | 20 |
| $autoresearch predict | 5 expert personas debate before implementation | N/A |
| $autoresearch learn | Scout codebase → generate docs or wiki → validate → fix loop | 10 |
| $autoresearch reason | Adversarial debate with blind judges until convergence | 8 |
| $autoresearch probe | 8 personas interrogate requirements until saturation | 15 |
| $autoresearch improve | Research ICP challenges, discover improvements, generate PRDs | 15 |
| $autoresearch evals | Analyze iteration results: trends, plateaus, regressions | N/A |
| $autoresearch regression | Regression stability gate: baseline vs candidate, verdict STABLE/UNSTABLE | N/A |
| Flag | Applies To | Purpose |
|---|---|---|
| Iterations: N | All looping | Set iteration count |
| Iterations: unlimited | All looping | Opt-in unbounded |
| --evals | All looping | Mid-loop checkpoints + final summary |
| --evals-interval N | All looping | Override checkpoint frequency |
| --chain <targets> | All | Sequential handoff after completion |
| --<subcommand> | All | Shorthand for --chain <subcommand> |
| --dry-run | Orchestrator | Print derived config + planned pipeline; no execution |
| --max-cycles N | Orchestrator | Hard ceiling on orchestration cycles (default 50) |
| --classic | Bare $autoresearch | Force Classic metric-loop mode |
| --auto | Bare $autoresearch | Force Orchestrator mode |
Activated when a plain-language goal is given without Metric:/Verify:. Classifies the goal into a Goal archetype — see references/orchestrator-routing.md for the archetype table and router decision table.
Two modes based on archetype:
Backed by scripts/orchestrate.sh (deterministic seam — all routing logic lives there). Subcommands exposed: classify, next-hop, units, plateau, screen-cmd, verdict, validate-state, screen-state-predicate.
scripts/orchestrate.sh classify "<goal>" → archetype label + mode.plan logic to produce a concrete Success predicate: exact shell command + expected output. For optimize-metric, run the full plan/wizard derivation internally.request_user_input showing: archetype, mode, concrete predicate (command + expected output), terminal choice (stop-at-verified vs proceed-to-ship). Misclassifications are caught here, not mid-run.screen-cmd; print projected cycle budget. Stop here if --dry-run.a. Assess state via cheap signals (last handoff.json, regression verdict, error count) + affected-test verify.
b. scripts/orchestrate.sh next-hop orchestrator-state.json → next subcommand.
c. Run subcommand (its own bounded inner loop).
d. Record per-hop outcome ∈ {progressed, no-op, failed, blocked}.
e. Fold hop's handoff.json into orchestrator-state.json.
f. scripts/orchestrate.sh units → recompute Units remaining.
CONVERGED.scripts/orchestrate.sh plateau orchestrator-state.json → true → stop + report PLATEAU.--max-cycles N) → stop + report CEILING.blocked/failed with no alternative route → checkpoint + stop + report BLOCKED.orchestrator-state.json — orchestrator-owned, additive. Tracks: goal, archetype, predicate, terminal-choice, units_remaining history, cycle count, per-hop pipeline log with outcomes, current incumbent. Each hop's handoff.json is unchanged (single-hop bridge); the orchestrator reads it and folds it in. Two clearly-owned state objects, no overlap.
--auto to ship; deploy always requires explicit user approval.localhost/127.0.0.1/container hostname, or database name carries _test/_ci suffix. Bare substring match does not qualify. Anything else refused.screen-state-predicate and refuses on refuse.screen-cmd.orchestrator-state.json; every cycle and every resume reuses that exact string so "done" is reproducible across runs.validate-state gates orchestrator-state.json (required fields + coarse types); a malformed ledger is not trusted to route from.pending_verify; next-hop routes to a verify hop (held-out / adversarial check) before DONE or ship. The verify hop never auto-approves ship.units returns unknown (e.g. runner crash) is not counted as zero-progress; repeated unknown routes to BLOCKED.Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take mxyhi/autoresearch from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.