「skill discovery」の検索結果

Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.

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Broad, pre-curation evidence reconnaissance for a declared Gaia skill, intake batch, upstream repository, or proposed generic capability. Run before choosing a discovery strategy or mapping topology, to give the curator independent research leads and counterevidence. Context only: never scores, grades, ratifies, ingests, or mutates the registry. Later ev-discovery and ev-pipeline phases validate/promote any selected leads.

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Build Opportunity Solution Trees using Teresa Torres' framework for structured product discovery. Use this skill when: - You need to map a desired outcome to opportunities, solutions, and experiments - You want to decide WHAT to build next based on user research and discovery data - You have workshop findings, pilot feedback, or user research to structure into actionable options - You need a visual tree diagram showing the path from outcome to testable experiments

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Eliciting and documenting a sales process before it is built in Salesforce: stage sequencing, entry/exit criteria per stage, win/loss analysis requirements, and stage transition rules. Trigger keywords: sales process design, stage discovery, entry criteria, exit criteria, stage gate, win/loss categorisation, sales methodology, pipeline stages, opportunity stage mapping, stage ladder, probability ladder, forecast category mapping, required fields per stage, stage swim lane, discovery workshop, handoff brief. NOT for configuring OpportunityStage, Sales Processes or Path in Setup — use admin/opportunity-management. NOT for cross-functional swim-lane maps — use admin/process-flow-as-is-to-be.

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Drafts California Superior Court discovery verification pages under CCP §§ 2030.250 and 2031.250 with proper CCP § 2015.5 perjury declarations. Trigger when the user needs a verification page for interrogatory or inspection/RPD responses, mentions California discovery verification, party vs. attorney signing, information-and-belief clauses, or fixing unverified responses. CA Superior Court only — not federal.

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Produces an attorney-ready memo from a corpus of legal documents supplied by the user. Use when a user shows up with a folder, zip, or vault of case documents and asks for a case summary, case evaluation, litigation package, intake memo, matter overview, or "can you summarize this case for me." The skill ingests the corpus into a searchable index, OCRs anything non-searchable, inventories and diagnoses the practice area, loads the appropriate practice-area playbook module(s) (PI/tort, commercial litigation, IP infringement, or user-authored extensions), iteratively searches the corpus across eight core dimensions plus any module-specific dimensions, defers specialized document clusters (depositions, medical records, discovery, liens) to dedicated sibling skills, and synthesizes a cited memo.

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Citation format and verification protocol for legal documents that draw on Bates-stamped source records. Defines the bracket citation format, multi-source citation rules, quotation handling, the verification pass that runs before output, and the [UNVERIFIED] flag protocol. Use this skill any time another skill produces a legal work product that cites Bates-stamped pages, including medical chronologies, deposition summaries, demand letters, case briefs, and discovery responses. Also use any time the user asks how to format a citation or verify that a claim is supported by the source.

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Workflow navigation assistant. Scans project state (plans, reviews, tests, git) and recommends the next step in the 7-phase pipeline. Use when asked "what should I do next?", "where am I?", "help", or at session start. NOT for domain complexity routing (see mk:scale-routing); NOT for skill discovery (descriptions handle that automatically).

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Reddit automation skill collection. Supports authentication, content publishing, search & discovery, social interactions, and compound operations. Triggered when a user asks to operate Reddit (post, search, comment, login, analyze, upvote, save).

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Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

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Do market research, user research, and product validation on Reddit with semantic search across 50K+ subreddits, 20M+ posts, and 40M+ comments via reddapi.dev - search by meaning, not keywords, no Reddit OAuth or app registration needed. Use when the user wants to research what people say on Reddit, find user pain points and complaints, validate a product or niche idea, do competitor and market research, track subreddit trends over a date range, or discover which subreddits discuss a topic. Also use when the user mentions 'Reddit research', 'Reddit 调研', 'search Reddit', 'subreddit discovery', 'niche validation', 'pain points', 'user complaints', or 'Reddit trends'. Requires REDDAPI_API_KEY. For B2B lead scoring, see reddit-leads; for a bare API reference, see reddit-search-api.

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Catalog and selection guide for Exasol tools, extensions, connectors, integrations, and architecture patterns. Use when the primary intent is comparison, discovery, support-status research, or architecture selection rather than executing a workflow; hand operational work to the selected dedicated skill. Covers deploy, load, explore, enrich, surface, and scale capability families, including named products with no dedicated skill of their own such as Lakehouse Turbo, the Exasol MCP Server, Governed SQL / Text-to-SQL MCP Server, Agent Control Plane, Extension Manager, Terraform and Ansible tooling, and BI, ETL, and warehouse integrations such as Databricks, SAP, Kafka, Power BI, and Tableau.

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Provider-neutral planner for synchronizing MCP configuration, skills and rule files across agent providers and app classes. It discovers evidenced local options and lets the user choose truth, targets, direction and conflicts.

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Prepares a discovery call brief from what the user has on a prospect (CRM record, inbound form, emails, notes, public material the user supplies): what is known with sources, gaps against the qualification dimensions, hypotheses to test, questions in priority order and what to listen for. Returns a DRAFT Markdown brief in the chat. Use when the user asks to "prep me for the discovery call with <prospect>", "what should I ask on this first call", "intro call brief", "questions for the qualification call" or "what do we know before we speak to them". Do not use for scoring leads against a rubric, use lead-qualification-scorer instead; for an existing customer's account review use account-plan-builder. Drafts for human review; never approves, authorises or signs off.

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Create a capture for ANY Estuary connector using dynamic schema discovery. Use when the user wants to capture from a source that doesn't have a dedicated skill (e.g., Kafka, Salesforce, HubSpot, Stripe, S3, GCS, Kinesis, or any of the 148+ connectors). Use when user says "capture from <source>", "stream from <source>", "connect <source> to Estuary", or "set up <source> capture" and no connector-specific skill exists.

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Use when working with Cyberark — cyberArk privileged access management for safe management, privileged account discovery, session monitoring, credential rotation status, and security audit. Covers Vault, PVWA, PSM, and CyberArk Privilege Cloud. Read this skill before any CyberArk operations — it enforces discovery-first patterns and strict read-only safety rules.

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Legacy compatibility entry for prompts or documentation that explicitly name `using-superpowers`. Route new skill-discovery workflows to `using-skills`; do not activate both entrypoints for the same task.

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Run Mom Test–style customer-discovery interviews to validate or kill an unbuilt idea — generate a non-leading interview guide, conduct or coach the conversations, and synthesize signal vs compliments. Load when the user asks to do customer discovery, run problem interviews, validate an idea with users, run a Mom Test, design an interview guide, or says "talk to customers", "validate the problem", "interview users", "Mom Test this", "did real users want it", "synthesize my interviews", "I just talked to N people". Sub-skill of `venture-exploration`. Hard-bans "would you use this?", solution-pitching, friend/family-only ICP, and treating compliments as validation. Calls `secure-*` before synthesizing any pasted external transcripts.

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Convert an existing find-XXXX SKILL.md into a preprocessor Python script, updating configs/<GAMEVER>.yaml and removing the old SKILL.md. Covers xref-string-based and LLM_DECOMPILE-based discovery patterns.

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This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.

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Build a bounded Agent Skill catalog across explicit discovery scopes and report collisions before loading instruction bodies.

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Uses Parallel CLI for web search, URL extraction, deep research, structured data enrichment, entity discovery, and recurring web monitoring. Best for requests that explicitly need current web evidence, academic-source discovery, repeated entity lookups, exhaustive reports, or ongoing change tracking.

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Ask real executives and domain experts a question through Instant Expert for a written answer or short call: practitioner knowledge, customer discovery. Free test mode; live sends need approval.

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This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.

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。