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Validate changesets in openai-agents-js using LLM judgment against git diffs (including uncommitted local changes). Use when packages/ or .changeset/ are modified, or when verifying PR changeset compliance and bump level.
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Compare research records you provide to see changes in facts, scores and judgments. Use when the user asks to investment review with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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Find connections between notes and update MOCs. Requires semantic judgment to identify genuine relationships. Use after /reduce creates notes, when exploring connections, or when a topic needs synthesis. Triggers on "/reflect", "/reflect [note]", "find connections", "update MOCs", "connect these notes".
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Apply Hunt and Thomas-inspired pragmatic programming rules when improving engineering judgment, feedback loops, DRY knowledge, orthogonality, automation, or adaptability.
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Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.
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Score one blog post (or a folder of posts) on a 5-category 100-point scale covering content quality, SEO, E-E-A-T, technical elements, and AI citation readiness. Runs the deterministic analyzer first, then adds judgment and prioritized Critical/High/Medium/Low fixes. Advisory style diagnostics never infer authorship or affect the score. Exports markdown, JSON or table; works with MDX, markdown, HTML or a URL. Use when the user asks to analyze, score, rate or check the quality of specific posts ("analyze blog", "blog score", "check blog quality", "rate this post"). For a site-wide health check (orphan pages, cannibalization, stale content, schema across all posts) use blog-audit instead.
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A medical-research-native literature reading skill for users with clinical, bioinformatics, translational, and basic experimental backgrounds. Use this skill whenever a user wants to read, analyze, critique, or interpret a medical or scientific paper — whether they provide a PDF, abstract, DOI, PMID, or just a title. Triggers include requests like \"analyze this paper\", \"critique this study\", \"is this a strong paper?\", \"give me similar studies\", \"prepare me for journal club\", \"help me understand this bioinformatics paper\", \"what are the weaknesses here?\", or \"turn this into a mind map\". Also activate for any downstream deliverables such as journal club kits, comparison tables, PI decision briefs, replication starters, or follow-up experiment designs. Do NOT treat as a generic summarizer — this skill performs structured evidence-type classification, track-specific critical appraisal, interpretation-boundary judgment, and research-grade follow-up generation.
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Assesses whether study results are trustworthy by auditing design integrity, sample structure, statistical handling, bias control, validation chain, and claim discipline. It identifies where results are robust, fragile, overfit, under-validated, or overclaimed. Always separate reported findings from reliability judgment. Never fabricate references, PMIDs, DOIs, trial identifiers, study features, or validation claims.
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Use when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment.
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Use when evaluating a business through Buffett-style ownership, owner earnings, durable moat, management quality, capital allocation, and margin-of-safety judgment.
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Monitor current news and reaction signals, then decide which are credible newsjacking opportunities for a client. Uses the local monitoring engine for evidence, but the skill owns PR judgment, brand safety, standing, decay, angle fit, and handoff.
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Cheap, high-recall first-pass filter that removes obvious junk from a detector candidate pool before expensive story-origin research and PR judgment. Decides keep, monitor_only, or reject — never ranks, writes angles, verifies dates, or decides whether to pitch.
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Use when an agent folder must pass the Agentlas Cloud 2-stage security scan (static rules + BYOK LLM judgment) before private sync or public publish, or when asked to run/interpret `hephaestus security scan`.
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Produces the reader-facing HTML artifact — report, dashboard, architecture view, data browser, or review workbench — evidence-backed, browser-verified. Use when the deliverable IS a visual HTML report, or the user asks for an HTML/web presentation. Load data-visualization-discipline for chart judgment. Not for chat status or Markdown prose unless asked to become a report; not for PowerPoint (deck-creator Route C).
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Run a real brainstorm — divergent generation without judgment, then convergent selection with explicit criteria — instead of listing ten obvious ideas and calling it creativity. Use when asked to brainstorm, generate ideas or options, explore a solution space, or name something. Produces a genuinely wide option set (including the weird tail), then a shortlist selected against named criteria with the rejects preserved.
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Manual intent elicitation skill. Use when the user asks to clarify a fuzzy idea, run an elicitation session, design an agent/skill/workflow, identify strategic tension, do a postmortem, align taste/brand direction, or turn vague judgment into an actionable Intent Brief. The skill asks 3–5 sharp questions first, then compiles answers into an Intent Brief and routes the result into system/workflow change. Never run automatically or on a schedule.
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Register a deferred decision in the debt registry. Trigger by judgment, not a marker scan, whenever a future reader would ask "why this way?": an unmade decision, stub, loosened type, bypassed check, swallowed error, a default picked "for now", or a TODO/FIXME/HACK/XXX marker. Trigger immediately whenever you defer work, or when the user invokes $add. Over-register freely; the developer drops with "drop A", "drop A,C", or "drop all".
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Explicit landing-page build and deploy operator. Loads marketing and frontend judgment, scaffolds the smallest suitable site, verifies it rendered, deploys to the configured target.
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The Power BI report design canon covering design identity, visual hierarchy and the 3-30-300 rule, layout/spacing/alignment, color discipline, chart selection, KPI and card design, tables and matrices, accessibility, and the closing design gate. The shared reference home for report design judgment, routed to by the create-pbi-report, pbir-cli, review-report, modifying-theme-json, and custom-visual skills. Load when committing a design identity or making a design, layout, color, chart-selection, or accessibility decision for a report.
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Extract and maintain global and method-specific mathematical-model assumptions from the problem frame, active method cards, data profile, and risk probes, while leaving necessity and impact judgments to the human modeler.
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Build one compact choice card at a genuine mathematical-modeling judgment point. Use before method screening, after a meaningful experiment, or before final claim/freeze approval so the human chooses the trade-off while AI handles mechanical consequences.
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Perform a structured maintainer-style PR review for the mariadb-operator repository. Gathers PR context, triages the change, and evaluates correctness, safety, pitfalls, backwards compatibility and code quality against the project conventions documented in AGENTS.md. Use whenever the user mentions a mariadb-operator PR number or URL and wants any kind of judgment on it — "review this PR", "what do you think of #1234", "is this safe to merge", "assess this diff", "take a look at this change" — even if they don't literally say "review".
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Initialize a PM Brain — a markdown-native second brain for a product operator (PM, product lead, founder, or anyone accountable for one product or initiative) doing judgment-heavy work with scattered inputs. Detects greenfield vs. migration mode, runs a focused interview, copies the deterministic scaffold into the working directory, populates placeholders from interview answers, runs a self-test, and commits. Use when invoked via `/pm-brain` or when the user asks to set up a PM Brain.
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Organize document evidence into auditable competing hypotheses, source-linked observations, an assessment matrix and document-linked discriminating tests. Use for bounded explanatory questions, documents that could resolve uncertainty, rejection history, source provenance, gaps and updates, including a withdrawn or corrected fact and which explanations and earlier judgments it puts back under review; not findings of guilt or predictions about people. Evaluation preview requiring human review.
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