Retrieve authoritative OpenAI API and platform documentation when an integration or claim needs current external evidence.
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。
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概要と使いどころ
Retrieve authoritative OpenAI API and platform documentation when an integration or claim needs current external evidence.
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。
Research competitors and generate a positioning and messaging comparison with content gaps, opportunities, and threats. Use when building sales battlecards, when finding positioning gaps and messaging angles competitors haven't claimed, or when a competitor makes a move and you need to assess the impact.
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Review a PR the way a seasoned maintainer would — build an independent model before seeing the diff, investigate the implementation and history, verify material claims, and return a concise briefing. Use for any PR review, self-review, or re-review.
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Turns marketing prompts into tested, versioned production assets: A/B prompt evaluation against structured test cases, immutable prompt version history with diffs, ready-to-use marketing prompt templates (ad copy, email campaigns, social posts, landing pages, SEO meta), and an LLM-governance playbook for marketing teams (claim discipline, disclosure rules, human-review gates). Use when a marketing team relies on AI-generated content and needs prompt quality to be measurable and safe — or when the user mentions 'prompt engineering,' 'improve my prompts,' 'prompt templates,' 'prompt versioning,' 'AI content workflow,' or 'AI governance for marketing.'
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Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the response-strategy moment. Surfaces GAP requirements explicitly — never invents claims. NOT free-form proposal narrative authoring, NOT contract redline, NOT marketing collateral.
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/cs:cpo-review <plan> — JTBD-driven interrogation of product roadmap, PMF signal, and portfolio focus. Use when committing a quarter's roadmap, deciding whether to kill a feature, or claiming PMF without a retention curve.
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Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard with industry tuning, tracking SLA compliance with credit-claim flags, classifying third-party risk across 4 risk vectors, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. Triggers on "vendor SLA", "vendor scorecard", "third-party risk", "TPRM", "vendor review", "supplier performance", "vendor health check", "renewal review".
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Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding, incident handoff, customer-onboarding, claims adjudication) in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time. Pairs Lean / Six Sigma / Theory-of-Constraints canon with deterministic stdlib-only Python tools to produce a process map, a ranked bottleneck list (with severity + root-cause hypothesis), and a cycle-time analysis (P50, P90, value-add ratio, Little's-Law throughput). Distinct from sales-pipeline, system-reliability (SLO), and strategic-OKR work — this is tactical process documentation for internal operations.
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Use when the user asks to deeply read a book, article, PDF, or document set; extract claims and evidence; build a knowledge map; or learn through Feynman explanation and recall. Covers quick, deep, map, Feynman, and whole-book reading modes.
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。
Screenshot or record a cmux window from the CLI, for a pull request, a bug report, or to see what the app actually looks like right now. Use when a change is visual, when a drag or an animation cannot be described in text, or when a reviewer needs evidence rather than a claim.
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 when working in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.
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Red-team a PRD, roadmap, or strategy by attacking its load-bearing assumptions before reality does. Steelmans then attacks each claim, ranks failure modes by impact × likelihood × cheapness-to-test, and returns the cheapest test and kill criteria for each. Use when stress-testing a plan, pressure-testing a strategy, challenging assumptions, or preparing a doc for executive review.
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Assess whether furniture fits in a measured Pascal room or layout. Use this skill for sofa, table, bed, cabinet, appliance, staging, placement, collision, clearance, or rotated-footprint questions. Produce a tool-backed spatial report that distinguishes footprint fit from unsupported height, door-swing, assembly, and delivery-route claims, and return insufficient evidence when dimensions or scale are missing.
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Recipe: write platform-native social content for Kortix (LinkedIn posts, X threads, carousels, Instagram, TikTok, Reels and Shorts video scripts, content calendars) and repurpose one long-form piece into many. Load kortix-brand first for voice, positioning and claims. This skill covers platform mechanics: limits, hooks, cadence, repurposing. Use when the user asks for a LinkedIn post, Twitter or X thread, carousel, social calendar, "what should I post", "repurpose this", a video hook, a reel or short-form video.
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Employee offboarding runbook for {{projectName}}. Detects newly marked departures via the {{hris_group}} group in Okta, then works one independent case per departure across Okta, Google Workspace, Google Drive, and GitHub — revoking access, transferring ownership, and reclaiming licenses — holding the ownership transfer for a human approval gate (never deleting an account) and posting the completed checklist to {{notify_channel}}.
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。
Find and read information on the open web — fan-out web/news/finance search plus full-page fetching and source extraction. Use to answer current questions, gather and cite sources, verify a claim, or pull text from specific URLs. Triggers: 'search the web', 'look this up', 'find sources on', 'what's the latest on', 'fetch this page', 'is it true that…', 'compare X vs Y'.
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。
Deep research agent skill. Use when the user needs thorough, scientific, truth-seeking research on any topic -- investigating claims, finding primary sources, synthesizing evidence, producing cited reports. Triggers on: 'research this', 'investigate', 'deep dive', 'find sources', 'what does the evidence say', 'literature review', 'fact check', 'analyze the research on', any request requiring multi-source investigation with citations.
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Build, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent coordination. Use this whenever a coding agent is unreliable across sessions — forgets context, drifts out of scope, claims "done" before tests pass, or starts each session inconsistently — or when creating or assessing AGENTS.md, CLAUDE.md, feature_list.json, init.sh, progress.md, or session-handoff files. Reach for it even if the user never says the word "harness."
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Adversarial analysis deploying parallel expert agents to stress-test ideas, strategies, and plans — decomposes into atomic claims, attacks them, then steelmans and counter-argues, producing severity-ranked findings with remediation. USE WHEN red team, attack idea, counterarguments, critique, stress test, devil's advocate, find weaknesses, break this, poke holes, strongest objection. NOT FOR collaborative debate to find best path (use Council).
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Hardens LifeOS tests via property/mutation testing. USE WHEN harden, hardening, property test, property based testing, PBT, fast-check, mutation test, mutation testing, Stryker, CRAP score, CRAP analysis, DRY scan, jscpd, acceptance test mutation, strengthen tests, sharpen ISCs, find bugs example tests miss, universal quantified claim, shrink counterexample, what bugs am I missing, test the tests, test of the test. NOT FOR writing new feature tests (use bun test directly), grading agent output quality (use Evals), UI verification with real Chrome (use Interceptor), finding security vulnerabilities, or building new functionality.
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Evidence-grounded context refresh: reads constitutional files, TELOS, and CURRENT_STATE/IDEAL_STATE dimension files via TelosFreshness, pulls observed data (Oura sleep/HRV, Conduit app-time, work registry, git, expenses via StateEvidence), and drives a peer conversation that opens with claim-vs-evidence contradictions, drafts corrections for ratification, and closes with a ComputeGap-grounded ideal-state review. Routes to ContextCheckin; Phase0Setup on fresh install. USE WHEN /interview, resume interview, context check-in, telos check-in, what's stale, stale data, freshness check, update current state, update my current state, state sync, statusline says interview due, interview due, review TELOS, update ideal state, quarterly context refresh, fresh LifeOS install, configure DA name. NOT FOR single edits (Telos), bulk intake (Migrate), identity-only.
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。
Three-layer bias analysis on any URL, file, or text — auto-fetches the content and any cited study, then audits data-level biases, source conflicts of interest, and journalism-added distortions, separating what the data supports from what's editorialized. USE WHEN bias analysis, analyze bias, bias check, check this study, who funded this, is this source biased, fact-check article, methodological flaws, source credibility, what's wrong with this claim. NOT FOR psychological author analysis, research synthesis (use Research), entity due diligence.
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 the full patent specification from claims and invention disclosure. Use when user says "撰写说明书", "write specification", "写说明书", "patent description", or wants to draft the complete patent specification.
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Get an external patent examiner review of a patent application. Use when user says "专利审查", "patent review", "审查意见", "examiner review", or wants critical feedback on patent claims and specification.
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。