「bli」の検索結果

Suede-affiliated comprehensive marketing planning across acquisition, activation, retention, referral, and revenue, sized to the actual team, budget, evidence, and stage. Use when the user needs a 90-day plan, 12-month roadmap, growth plan, or go-to-market operating document. NOT FOR: isolated channel execution (use the relevant public Suede skill), uncommitted tactic brainstorming (use suede-marketing-ideas), or positioning discovery alone (use suede-product-marketing).

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Run outcome-focused Firecrawl workflows that produce deliverables such as research reports, literature reviews over published papers, SEO audits, QA reports, lead lists, knowledge bases, website design systems, and other structured web-data artifacts. Use when the user wants Firecrawl to complete a business, marketing, product, or creative workflow rather than merely scrape a page or integrate API calls into code.

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Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

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Search an index of public repositories, GitHub issues, merged pull requests, repository READMEs, and curated documentation sites. Use when a programming question needs external documentation or upstream evidence.

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Extract market, financial, earnings, industry, and company metrics with Firecrawl. Use when the user asks for market research, industry trends, public company data, financial comparisons, earnings research, or structured market reports.

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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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Ingest public or authenticated knowledge bases and docs portals with Firecrawl browser. Use for JS-heavy docs, login-gated portals, paginated help centers, support knowledge bases, or structured JSON/markdown extraction from documentation sites.

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Axone deployment workflows with cargo-make, cw-orch, and Abstract. Use when publishing modules, installing them on accounts, running local chain tasks, or inspecting deployments.

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。

Guide for writing Rust doc comments that produce accurate generated contract documentation. Use when editing Instantiate/Execute/Query/Response types or any public schema-facing API.

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Draft, edit, and publish blog posts for e9n.dev. Use when creating new posts, editing drafts, or refining existing content. Handles Eleventy frontmatter, Tailwind formatting, and Espen's authentic voice.

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Manage npm packages — install, publish, version bump, audit, and run scripts using the npm tool.

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Take screenshots and interact with web pages using a headed Playwright browser. Use when you need to visually inspect a URL, capture a screenshot, interact with a page (click, type, scroll), or verify what a page looks like rendered. **Triggers — use this skill when:** - You need to screenshot a URL (Penpot share link, localhost, public site) - User says "show me", "how does it look", "take a screenshot" - You want to visually verify your own work (e.g. after creating Penpot designs) - User asks to review a live page or prototype - You need to interact with a page (click buttons, fill forms, trigger states)

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Reverse-engineer a design system from a live website (public URL or localhost). Extracts colors, typography, spacing, shadows, radii, breakpoints, and component patterns using a headed Playwright browser. Captures screenshots of pages, components, and interactive states at real device resolutions. Produces structured design tokens and optionally seeds a Penpot project. **Triggers — use this skill when:** - User says "extract design system from [url]" - User asks to "reverse-engineer the styles from [site]" - User says "build a design system based on [website]" - User asks to "pull the design tokens from [url]" - User says "analyze the design of [site]" - User asks to "import styles from [website] into Penpot" - User points at a URL and asks about its colors, fonts, spacing, or components

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。

Brainstorms and debates approaches, then drives toward an actionable decision. Use whenever someone needs a thinking partner for a decision they're facing: 'discuss', 'debate', 'brainstorm', 'weigh options', 'tradeoffs', 'should I do X or Y', 'help me decide', 'I'm torn between', 'sanity check my thinking', or 'what do you think about'. The user must be asking for help reasoning through a choice — not asking to build, fix, evaluate, plan, or modify something (even if the topic involves this skill itself). Picks the right decision lens, surfaces tradeoffs and blind spots, pushes back when reasoning is genuinely weak, and never implements.

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。

Redact text from PDF documents for blind review anonymization

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Generate structured 8-section validation reports with verdict (GOOD/BAD/NEEDS MAJOR WORK), strengths, critical flaws, blindspots, and concrete path forward. Use after strategic-cto-mentor has completed validation analysis and needs to produce final deliverable.

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。

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

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。

Write, run, and analyze structured test suites for Agentforce agents — functional AND security. TRIGGER when: user writes or modifies test spec YAML (AiEvaluationDefinition); runs sf agent test create, run, run-eval, or results commands; asks about test coverage strategy, metric selection, or custom evaluations; interprets test results or diagnoses test failures; asks about batch testing, regression suites, or CI/CD test integration; requests security testing, OWASP LLM Top 10, red-teaming, penetration testing, prompt-injection tests, a security grade, or a vulnerability assessment of an agent. DO NOT TRIGGER when: user creates, modifies, previews, or debugs .agent files (use agentforce-generate); deploys or publishes agents; writes Agent Script code; uses sf agent preview for development iteration; analyzes production session traces (use agentforce-observe); performs a static safety review of .agent file content (use agentforce-generate Section 15).

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Analyze production Agentforce agent behavior using session traces and Data Cloud, and manage Agent Health Monitoring (AHM) alerts. TRIGGER when: user queries STDM session data or Data Cloud trace records; investigates production agent failures, regressions, or performance issues; asks about session traces, conversation logs, or agent metrics; wants to reproduce a reported production issue in preview; runs findSessions or trace analysis queries; creates, lists, updates, or deletes an AHM data alert on an agent metric (escalation rate, deflection, etc.); asks why an alert is not firing or wants to check whether alerts have fired (notification counts, or the per-alert Incidents view). DO NOT TRIGGER when: user creates, modifies, or debugs .agent files during development (use agentforce-generate); writes or runs test specs (use agentforce-test); uses sf agent preview for local development iteration; deploys or publishes agents.

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Use before writing any new function, helper, component or module - find what the repository, the standard library and the installed dependencies already provide, and use an established library instead of hand-rolled code for a non-trivial problem

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Use when adding controls, menus, HUD, subtitles or effects - input through named actions with rebinding and controller support per engine, input buffering, and the accessibility floor (remapping, colour-blind safe cues, subtitles, text scale, reduced motion and flashes).

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Use when a batch (desktop or mobile) release reaches awaiting_verdict or was rolled back - read-only checks that the published artifact really exists and is served, and the exact yank step for a bad tag

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Phase F of a WinForms-to-Avalonia migration: evolve the Avalonia trunk after cutover without reintroducing WinForms coupling or bypassing established layers. Use only when an explicit migration has an active Avalonia trunk and a concrete product backlog, or when the orchestrator routes here. Select work from repository evidence; do not assume particular entry points, integrations, settings, or extension mechanisms exist.

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Find, rank, and safely remove accidental codebase complexity by proving real consumers, dynamic entrypoints, compatibility obligations, duplicate representations, speculative surfaces, and lifecycle ownership. Use when asked to simplify or clean up a repository, reclaim code entropy, reduce over-engineering or redundancy, find deletion candidates, collapse duplicate state/APIs, remove dead or added-then-abandoned code beyond static-tool output, or implement an evidence-backed simplification pass in any language or stack. Also trigger for 代码化简、熵回收、删代码、清理冗余、收敛抽象、去除过度设计. Do not use as a performance audit unless simplification is the stated goal.

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。