2.4천건 · 관련도순
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
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Create, edit, or debug parametric 3D CAD parts in CadQuery (Python) that export to STEP for SolidWorks. Use when the request involves CadQuery, .step/.stl export, or modelling a physical part — enclosure, bracket, PCB, motor mount, cam, gear. Also use when a STEP will not open in CAD, or geometry looks correct in STL but is invalid as a solid. Applies a verification discipline before export and documented OCC pitfalls.
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Plan, verify, and track demo/marketing video production in Busabase — idea to hook/pain-point/storyboard, codebase claim verification, recording progress, post-production handoff, and HyperFrame (Remotion) linkage. Use when the user invokes $kelly-demo-video-factory or /kelly-demo-video-factory, wants to plan a product demo video, write a storyboard, verify a video script's product claims against the codebase, track which shots are recorded, or hand a finished storyboard off to editing/Remotion.
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Build, maintain, and run conformance tests for canonical App-in-Skill projects created by kelly-app-skill-creator. Use when a Kelly app skill needs contract checks, local server smoke tests, responsive browser acceptance, temporary open-source Busabase integration, environment-gated Busabase Cloud OAuth verification, lazy provisioning checks, persistence tests, AirApp parity tests, or CI coverage. Keep app creation in kelly-app-skill-creator and own only the reusable test harness, per-skill fixtures, execution gates, diagnostics, and truthful pass/fail/skip reporting.
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Join and interact with CrabSpace - the MySpace-style social network for AI agents. Use when creating a profile, customizing appearance, managing friends, or posting on comment walls. Handles registration, tweet verification, profile updates, and social features.
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Manual-only orchestrator for medium-to-large software development. Turns a broad goal into PR-sized and operational nodes with verification gates, then coordinates approved execution across follow-up prompts. Activate only when the user explicitly invokes my-epic; once activated, keep orchestrating that epic for the rest of the session. Do NOT use for an uninvoked planning or implementation request, a single small bug fix, one obvious PR, pure code review, ordinary SDD work that fits in one spec/PR, or implementing an epic during the same first call that created it.
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Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.
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Configuring Google Cloud Identity-Aware Proxy (IAP) to enforce per-request identity verification for Compute Engine, App Engine, Cloud Run, and GKE services using access levels, context-aware policies, and programmatic access with service accounts.
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Check your work with a verification subagent. Spawns a verifier that reviews diffs, runs builds and tests, and evaluates correctness. Use when asked to "check work", "verify changes", "self-verify", "/check", "/verify", "/check-work", or "/self-verify".
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Rigorous methodology for evaluating ML models on established benchmarks. Covers proper train/val/test splits, baseline verification from original papers, exact metric formula discrepancies, data-leak detection checklist, multi-seed robustness, and honest reporting templates. Use when claiming to beat published baselines, writing methods papers, or auditing existing results.
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Optimize ToolUniverse skills for better report quality, evidence handling, and user experience. Apply patterns like tool verification, foundation data layers, disambiguation-first, evidence grading, quantified completeness, and report-only output. Use when reviewing skills, improving existing skills, or creating new ToolUniverse research skills.
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Strict SMILES validation, structural comparison, and modification verification. Catches invalid LLM-generated molecules.
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Zero-knowledge proofs and privacy patterns on Stellar. Covers Groth16 verification in smart contracts via BLS12-381 host functions (CAP-0059, available), the BN254 + Poseidon proposals (CAP-0074/0075, status-sensitive), and concrete toolchain walkthroughs for Circom (on-chain verifiable today), Noir, and RISC Zero (attestation pattern until BN254 lands). Use when building privacy-preserving applications, ZK-verifier contracts, or wiring a proving toolchain to Stellar.
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Walk through the devnet → mainnet deployment checklist for a Soroban contract or Stellar dApp. Use when a user says "deploy to Stellar mainnet", "going live on Stellar", "deploy my Soroban contract", "Stellar production deployment", "mainnet checklist", or "ship it on Stellar". Covers pre-deployment verification, deployment mechanics with stellar CLI, and post-deployment monitoring with Soroban-specific gates.
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Pre-PR verification for VenTu — tests, data validation, static build, and e2e for the touched surface. Use before opening any PR. For visual UI checks also load ventu-verify-ui.
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Review changes for correctness, security, accessibility, and performance. Use for scoped quality reviews or verification plans; bug fixes use oma-debug.
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Ralph - persistent self-referential execution loop wrapping ultrawork with independent verifier verification
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Automated CLI-based parallel agent execution — spawn subagents via Gemini CLI, coordinate through MCP Memory, monitor progress, and run verification
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Design AI content detection systems for authenticity verification. TRIGGERS - Use when user needs help with ai-content-detector related tasks.
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Write, review, or audit this repository's technical documentation, including README.md, CONTRIBUTING.md, root and scoped AGENTS.md files, docs pages, and documentation drift. Use for source-backed documentation authoring, behavior verification, and cross-surface consistency. Do not use for code review, deslop diff cleanup, or whole-page rewrites, splits, or reorganizations handled by docs-refactor.
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Run Unity Test Runner and report detailed results. Use for EditMode/PlayMode tests, change verification, or failure diagnosis.
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Keep GPT-5.6 and other coding-agent work proportional to the request by locking scope, choosing the smallest sufficient implementation, matching verification to risk, and stopping when success is proven. Use for implementations, bug fixes, refactors, reviews, or maintenance where scope creep, speculative abstractions, unrelated cleanup, repeated test runs, unnecessary dependencies, or polishing beyond the request are risks.
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Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.
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Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.
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