AI agent self-correction mechanisms: error detection, validation loops, recovery strategies, confidence scoring, and iterative refinement
日本語の概要は準備中です。原文の説明を表示しています。
374 件 ・ 関連度順
概要と使いどころ
AI agent self-correction mechanisms: error detection, validation loops, recovery strategies, confidence scoring, and iterative refinement
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill for any marketing research, product positioning, copywriting research, or audience profiling task. Triggers include: "research my product", "develop my value proposition", "profile my avatar", "understand my market", "create a unique mechanism", "market awareness", "market sophistication", "ideal customer profile", "ICP research", "positioning research", "copywriting research", "features and benefits", "competitor research", "competitive analysis", or any request to deeply research a product or audience for marketing purposes. Use this skill proactively whenever a user wants to prepare materials for sales copy, landing pages, ads, email sequences, or any persuasion-focused content. If a user says "help me understand my market", "I need to figure out my messaging", "who is my customer", or "what makes my product different", this skill applies immediately.
日本語の概要は準備中です。原文の説明を表示しています。
Turn one line ("a turbofan jet engine", "a mechanical watch", "an LVAD heart pump") into a photoreal, physics based, interactive 3D simulation of that machine in a single HTML file, plus a 20 to 30 second film to post it. Real proportions in metres, real materials (PBR metals, paints, polymers, glass), studio lighting with soft shadows, moving parts driven by a small solver that computes real numbers (thrust, torque, rpm, flow, pressure, efficiency), and modes to explode it, cut it open with clean section caps, x-ray it, slow it down, label it and break it. Use this whenever someone asks to build, simulate, visualise, explain or "show how X works" for any machine, engine, mechanism, device, instrument or piece of hardware, wants an interactive 3D model or a cutaway, or wants a video of a machine for a post, even if they never say "simulation" or "three.js".
日本語の概要は準備中です。原文の説明を表示しています。
Execute comprehensive client-side injection vulnerability assessments on web applications to identify XSS and HTML injection flaws, demonstrate exploitation techniques for session hijacking and credential theft, and validate input sanitization and output encoding mechanisms.
日本語の概要は準備中です。原文の説明を表示しています。
Nature-style materials science manuscript reviewer skill for testing materials design, synthesis, processing, structure-property, mechanism, stability, scalability, computational prediction and application claims against materials evidence chains.
日本語の概要は準備中です。原文の説明を表示しています。
Nature-style chemistry manuscript reviewer skill for testing synthesis, catalysis, chemical biology, molecular/materials chemistry and analytical claims against identity, purity, controls, selectivity, mechanism, scope, reproducibility and quantitative comparison.
日本語の概要は準備中です。原文の説明を表示しています。
Nature-style atmospheric science manuscript reviewer skill for testing observation, reanalysis, model, aerosol-cloud-radiation, extreme-event, circulation-mechanism and attribution claims against their physical evidence chain.
日本語の概要は準備中です。原文の説明を表示しています。
Derive this project's own integration conventions from what the code already does, draft them as a wiring contract, and hold new work to it. Closes the built-but-not-wired gap at L3 (walking skeleton) — a mechanism that ships and is never called reads green in every other check.
日本語の概要は準備中です。原文の説明を表示しています。
Structures earnout and contingent payment mechanisms with milestone definitions, measurement periods, and payout scenarios. Use when modeling earnouts, designing milestone-based payments, or valuing contingent consideration.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes inflation protection mechanisms in infrastructure with CPI-linked revenues, index-based contracts, and real return modeling. Use when modeling inflation linkage, analyzing CPI adjustment, or evaluating real return profiles.
日本語の概要は準備中です。原文の説明を表示しています。
Structures post-offering stabilization with overallotment option exercise, market support, and penalty bid mechanisms. Use when managing stabilization, exercising greenshoe options, or analyzing aftermarket support.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluates deal protection mechanisms including break-up fees, no-shop clauses, matching rights, and force-the-vote provisions. Use when analyzing deal protections, negotiating break fees, or assessing termination provisions.
日本語の概要は準備中です。原文の説明を表示しています。
Run Claude Code in autonomous iteration loops until task completion — PRD-based feature development, test coverage improvement, lint fixing, documentation generation, dataset creation, or framework migrations. Uses in-session loop mechanism with specialized templates. Triggers on autonomous loop, iterate until done, run until passing, keep going until, ralph, PRD execution.
日本語の概要は準備中です。原文の説明を表示しています。
Implement a generative diffusion model (DDPM or score-based) with noise scheduling, U-Net architecture, training loop, and sampling procedures including DDIM acceleration. Use when building a generative model for image, audio, or molecular synthesis; implementing DDPM from a research paper; adding a custom noise schedule or conditioning mechanism; replacing a GAN-based generator with a diffusion alternative; or prototyping before scaling with production frameworks like diffusers.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze magnetic levitation systems by applying Earnshaw's theorem to determine whether passive static levitation is possible, then identifying the appropriate circumvention mechanism (diamagnetic, superconducting, active feedback, or spin-stabilized). Use when evaluating maglev transport, magnetic bearings, superconducting levitation, diamagnetic suspension, or Levitron-type devices. Covers force balance calculations, stability analysis in all spatial and tilting modes, and Meissner effect versus flux pinning distinctions.
日本語の概要は準備中です。原文の説明を表示しています。
One to three sentences describing what this skill accomplishes, followed by key activation triggers. This field is the primary mechanism agents use to decide whether to activate the skill — it is read during discovery before the full body is loaded. Start with a verb. Include the most important "when to use" conditions inline. Max 1024 characters.
日本語の概要は準備中です。原文の説明を表示しています。
Query the ChEMBL database web services for measured bioactivity data, compound records and calculated properties, targets, assays, mechanisms of action, drug indications and warnings. Use this skill to build curated SAR or QSAR datasets for a target, look compounds up by SMILES, InChIKey, name, or ChEMBL id, run similarity and substructure searches, and check what chemistry is already known against a protein. Also trigger when a query mentions ChEMBL ids (CHEMBL...), pChEMBL values, IC50/Ki/Kd/EC50 retrieval, assay confidence scores, or ebi.ac.uk/chembl.
日本語の概要は準備中です。原文の説明を表示しています。
Query the Open Targets Platform GraphQL API for target-disease associations, genetic and clinical evidence, tractability and safety liabilities, target prioritisation metrics, known drugs and mechanisms of action, and disease ontology. Use this skill for target identification and validation, target-disease evidence review, druggability assessment, drug repurposing, and resolving gene, disease, and drug names to Ensembl, MONDO, and ChEMBL identifiers. Also trigger when a query mentions Open Targets, platform.opentargets.org, association scores, tractability buckets, or api.platform.opentargets.org.
日本語の概要は準備中です。原文の説明を表示しています。
chrome-devtools-mcp launcher — a single bash script that resolves Playwright's bundled Chrome-for-Testing and Node.js directly through Nix. See repo README for usage, override mechanisms, and version compatibility.
日本語の概要は準備中です。原文の説明を表示しています。
Hard-gated ideation for an Arbor research run. Load at the START of every IDEATE round, before drafting any hypothesis. Enforces the PI mindset (mechanism over knob), the four-question first-principles probe, the kill-filter, and the four-line hypothesis format. Ported from Arbor's idea_drafting + first_principles_probe.
日本語の概要は準備中です。原文の説明を表示しています。
Design reliable, safe, and trustworthy agent systems that fail gracefully and operate within bounds. Use when building guardrails, handling edge cases, preventing harmful outputs, monitoring for failures, implementing safety constraints, or designing error recovery. Covers failure modes, constraint systems, oversight mechanisms, and safety validation.
日本語の概要は準備中です。原文の説明を表示しています。
Guidelines for designing tools and action spaces for AI agents. Use when building agent harnesses, designing tool interfaces, creating elicitation mechanisms, or optimizing agent-tool interactions. Covers progressive disclosure, tool design patterns, and lessons from Claude Code development.
日本語の概要は準備中です。原文の説明を表示しています。
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
日本語の概要は準備中です。原文の説明を表示しています。
Systematically remove malware, backdoors, and attacker persistence mechanisms from infected systems while ensuring complete eradication and preventing re-infection.
日本語の概要は準備中です。原文の説明を表示しています。