「find」の検索結果

Produce the Part 5 client validation document: evidence-cited findings for client decisions. "prepare v1 findings for client review"

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Maps every competitor and the gap they leave. Finds the direct competitors, indirect ones and the substitutes a buyer would use instead, from public sources only, and records what each sells, at what price, how they position themselves and what their customers complain about in public reviews, every fact with a link. Ends with a positioning map and the gap the new business can own. Use when the user says "who are my competitors", "is this market crowded", "what else is out there", "competitor analysis", "find the gap", or "who am I up against".

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Adversarial premortem for England & Wales civil litigation - builds the strongest version of a case, then attacks it from four angles to find where it loses before opposing counsel does. Runs an adversarial premortem on a UK litigation matter. Builds the strongest version of the case, then attacks it from four angles — procedural, substantive, evidentiary, strategic — to find where it actually loses. Returns a ranked stress-test brief: failure scenarios, evidence inconsistencies, blind spots, mitigations, and one brutal one-sentence verdict. Use before issue, before settlement negotiations, before a litigation-funder pitch, or before deciding whether to take a case.

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Use this skill when asked to find, cite, analyze, or summarize Icelandic court decisions. Triggers on requests involving Hæstiréttur (Supreme Court), Landsréttur (Court of Appeal), Félagsdómur (Labour Court), héraðsdómur (District Court) case law, or Icelandic legal precedent research.

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Adversarially stress-tests a legal text — a contract, statute, regulation, or judicial opinion — for interpretive ambiguity: it finds the seams where the people governed by it will later disagree about what it means and turns each into a concrete dispute scenario with both sides' arguments, the likely outcome, and a fix. Use it whenever someone wants to pressure-test, red-team, audit, or find weak spots, loopholes, gaps, ambiguities, or drafting problems in a legal document; whenever a drafter wants to tighten a contract, statute, regulation, or opinion before it issues; whenever a litigator wants to mine an opinion or contract for arguments; or whenever someone hands over a legal text and asks where it will be fought over or for issue-spotting. Trigger it for contract review, statutory-ambiguity analysis, judicial-opinion scope analysis, and drafting QA — even if the user never says "stress-test" or "ambiguity."

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Advanced file finder with type detection and filesystem extraction for analyzing firmware and extracting embedded filesystems. Use when you need to analyze firmware files, identify file types, or extract ext2/3/4 or F2FS filesystems.

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Expert collection-loop systems for collectible IDs, scavenger hunts, completion archives, nearest-item compass UI, hidden spawners, and persistent find-all-X progress. Use when implementing collectibles, scavenger hunts, completion% archives, or compass-guided item hunts. Keywords: collectible_id, scavenger_hunt, collection_manager, collection_compass, completion_archive, hidden_item_spawner, find_all, collectible_item.

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Expert blueprint for real-time strategy games including unit selection (drag box, shift-add), command systems (move, attack, gather), pathfinding (NavigationAgent2D with RVO avoidance), fog of war (SubViewport mask shader), resource economy (gather/build loop), and AI opponents (behavior trees, utility AI). Use for base-building RTS or tactical combat games. Trigger keywords: RTS, unit_selection, command_system, fog_of_war, pathfinding_RVO, resource_economy, command_queue.

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Use *before* starting work in a domain you don't know well, to surface the "unknown unknowns" — the things you don't even know to ask about — and learn just enough to prompt and decide well. Implements the "blind spot pass" pattern from Anthropic's Fable "finding your unknowns" field guide. Triggers when you say "I'm new to this", "I don't know what to ask", "teach me before we start", "blind spot pass", "unknown unknowns", "find my unknowns", or the Korean "내가 뭘 모르는지 알려줘" / "이 분야 처음인데" / "먼저 가르쳐줘" / "블라인드 스팟", or when you hand off a task while admitting you're a non-expert in that field (color grading, video editing, legal, tax, finance, design, an unfamiliar codebase, etc.). Do NOT use for simple factual questions, domains you already know, or directly-actionable work — answer those directly or route to planner / architect.

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Expert collection-loop systems for collectible IDs, scavenger hunts, completion archives, nearest-item compass UI, hidden spawners, and persistent find-all-X progress. Use when implementing collectibles, scavenger hunts, completion% archives, or compass-guided item hunts. Keywords: collectible_id, scavenger_hunt, collection_manager, collection_compass, completion_archive, hidden_item_spawner, find_all, collectible_item.

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。

Expert blueprint for real-time strategy games including unit selection (drag box, shift-add), command systems (move, attack, gather), pathfinding (NavigationAgent2D with RVO avoidance), fog of war (SubViewport mask shader), resource economy (gather/build loop), and AI opponents (behavior trees, utility AI). Use for base-building RTS or tactical combat games. Trigger keywords: RTS, unit_selection, command_system, fog_of_war, pathfinding_RVO, resource_economy, command_queue.

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FLOW framework integration — evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO prompts.

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Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

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The scDblFinder package gathers various methods for the detection and handling of doublets/multiplets in single-cell sequencing data (i.e. multiple cells captured within the same droplet or reaction volume). It includes methods formerly fou

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Profitable niche discovery for Amazon sellers. Identifies underserved markets with high demand but low competition. Analyzes market gaps, emerging segments, and untapped opportunities across categories. Use when the user asks about finding niches, profitable markets, underserved segments, market gaps, blue ocean opportunities, niche research, or what markets to enter on Amazon.

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Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".

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Find people actively engaging with competitor LinkedIn posts. Given a website URL, discovers competitors, fetches their company and employee posts, collects all commenters and reactors, and outputs a deduplicated CSV of engaged prospects. Use when someone wants to find leads from competitor engagement, build outreach lists from LinkedIn activity, or analyze who interacts with competitor content.

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Use the Blitz API to find decision-makers at specific companies when you already have a list of company domains. Best for SMB owner-finding, domain-to-people lookup, or supplementing Prospeo results. Outputs a CSV you can feed to the /list-builder Phase 5 or directly to /cold-email-starter-kit for Smartlead upload. Use when your targeting is company-first (not title-first).

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Find lookalike companies via DiscoLike's 65M+ business domain database. Search by seed domains ("find companies like clay.com and apollo.io") or natural-language ICP text ("B2B cold email outreach"). Supports negation domains (exclude competitors/existing customers) and country filtering. Use when you already know 3-10 reference companies and want hundreds more that look like them. Outputs CSV ready for /blitz-list-builder or the email waterfall.

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Build an influencer marketing strategy — finding influencers, briefing, contracts, deliverables, performance tracking, micro vs macro strategy, outreach, and FTC compliance. Use when the user says "influencer marketing", "influencer strategy", "work with influencers", "influencer outreach", "influencer brief", "find influencers", "micro influencer", "macro influencer", "nano influencer", "creator marketing", "brand ambassador", "influencer campaign", "influencer collaboration", "seed influencers", "gifting influencers", "paid influencer", "influencer ROI", or wants to use influencers or creators to grow the brand.

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Find the cheapest award dates for a route over a date range. Searches seats.aero across all programs, groups by date, and shows a calendar grid of the best deals. Use when dates are flexible and you want to find the sweet spot.

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Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

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Review uncommitted code changes to find unreasonable design, unfinished requirements, potential bugs, missed reuse opportunities, and optimization opportunities. Use when the user asks for a review of pending, uncommitted, or unpublished code changes and expects both findings and concrete improvements.

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Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.

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