「fid」の検索結果

EU Compliance Officer for MiFID II investment firms and IDD insurance distributors. Implements compliance frameworks, ensures National Competent Authority reporting, conducts product governance oversight, manages suitability and appropriateness testing, reviews marketing and inducements, coordinates cross-border passporting compliance, implements GDPR data protection, conducts AML (5AMLD/6AMLD) monitoring, and prepares for NCA inspections. Use for compliance manual development, MiFID II/IDD implementation, or ESMA guideline interpretation.

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Browsertrix Crawler is a browser-based crawling system from Webrecorder for high-fidelity site capture, QA replay analysis, and configurable crawl behavior. It runs complex crawls in a single Docker container and uses Puppeteer plus Chrome DevTools Protocol under the hood.

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。

Writing engine that audits and rewrites prose for AI-resistance, fidelity, and mechanical tell removal.

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。

Increase visual impact, contrast, personality, and compositional confidence when a design feels bland, generic, or too safe. Use when the design needs more energy, confidence, or memorability—not when the real problem is clutter, over-intensity, or micro-detail polish.

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Analyze pre-trained generative diffusion models (Stable Diffusion, DALL-E, Flux) by computing quality metrics (FID, IS, CLIP score, precision/recall), inspecting noise schedules, extracting and visualizing attention maps, and probing latent spaces. Use when evaluating a pre-trained generative diffusion model's output quality, comparing noise schedule variants, analyzing cross-attention patterns for text-conditioned generation, interpolating between latent codes, or detecting out-of-distribution inputs.

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AI multi-path reasoning coherence using bee democracy — independent evaluation of competing approaches, waggle dance as reasoning-out-loud, quorum sensing for confidence thresholds, and deadlock resolution. Use when forage-solutions has identified multiple valid approaches and a selection must be made, when oscillating between options without committing, when justifying an architecture or tool choice with structured reasoning, or before an irreversible action where the cost of the wrong choice is high.

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Use when an authorized reference surface needs a clean-room frontend reconstruction across static, motion, and responsive fidelity. Not for styling or component work without a reference surface.

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Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.

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Reasoning data lost across agent steps and missing low-confidence fallback Keywords: sqlite, triangulation, escalation, confidence

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"Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction. Use this skill when the user needs to rank products by ratings, sort content by approval rate, or build a 'best rated' list that accounts for sample size — even if they say 'rank by star rating', 'best rated with few reviews', or 'confidence-adjusted rating'.".

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Audits whether a machine-readable regelrecht law model is faithful to the LETTER of the wettekst — and strictly separates the wettekst (leading) from the toelichting (Nota/Memorie van Toelichting; explanatory, not a norm). Runs in critical passes per article/lid and detects four deviation classes: toelichting-bleed (a modeled criterion that the letter only states as an open norm, or not at all), missing verbatim elements (a word/condition such as a "tenzij" or a qualifier dropped from the model), wrong legal_basis anchoring (an endpoint hung on a "kapstok"-article while the operative norm lives elsewhere), and verbatim-drift in text: (an ingetrokken/older redaction). Also detects positief-lid vs uitsluitings-lid conflicts and checks the chapeau for an explicit derogation rule ("zo nodig in afwijking van het eerste lid") before judging precedence. Classifies every finding as modelfout (fix), wettekst-gevolg (report, do not fix), or letter-vs-toelichting-question (jurist decides what is leading + revision signal). Use when the user wants to know if a model is "dicht bij de letter", mentions letter vs toelichting/bedoeling, fidelity, "natuurgetrouw", or before trusting feature outcomes.

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Fierce autonomous internal co-founder. Bounded web research for evidence-backed improvements. Structured idea formulation with self-critique filter that rejects ideas not serving the goal. Auto-implements high-confidence aligned improvements, proposes medium-confidence ideas for approval. Evaluates viral coefficient, AI search visibility (GEO), and solo SaaS economics. Considers higher pursuits: employing disabled people, spiritual tech investigation, 99% wealth donation ethos.

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Turn any still image into a professional motion graphic through the Novoads API on Seedance 2.5. Covers how to read a reference image, motion vocabulary for any image type — UI, marketing hero, flat-lay, key art, collage, product, character — the prompt clauses that control camera, timing, frozen regions and text fidelity, and the upload mechanics. Use whenever the user supplies an image and wants it animated, moving, or turned into video — including "animate this", "turn this into a motion graphic", "make this move", "この画像動かして", "モーショングラフィックにして", "I want the cards to pop in", "I want the bars to slide up", or when they describe motion beats for a static image. Also use when asked to write a Seedance prompt for an existing image. Do NOT use for text-to-video with no source image, restyling existing footage (this skill takes no video input), cloning a reference video (use clone-video-ad), or a product photo that should seed a new scene rather than move as-is (use novoads-api).

Convert between LaTeX and Microsoft Word for academic manuscripts in either direction, and assemble .tex from mixed sources. Fires on: converting .tex/LaTeX to Word/.docx ("tex to docx", "latex to word", "tex2docx", "convert to word", "pandoc convert"); converting .docx manuscripts to LaTeX for editing and back ("convert to latex", "manuscript", "footnotes", "reference doc", the docx-to-tex-to-docx round-trip / academic paper editing pipeline); high-fidelity delivery where plain pandoc loses tables, mangles cross-references, or fails on custom macros — booktabs/regression tables, OMML equations, cleveref, \estauto, \@@input, \thanks, TikZ, native Word tables, longtable, siunitx; and building .tex from mixed PDF/docx/LLM-generated sources. Replaces and reroutes the retired skills manuscript-editing-template-latex, latex-to-docx-fidelity, tex2docx, and latex-from-mixed-sources.

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Security-focused code review identifying high-confidence exploitable vulnerabilities with two-axis severity/confidence scoring, OWASP 2025 alignment, per-finding Haiku verification, and false positive filtering. Optional GitHub PR posting. Use when user runs /security-review, /review:security-review, requests a "security review", "security audit", "vulnerability scan", or mentions "find vulnerabilities", "check for exploits".

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Structured multi-hop web research with explicit confidence gating — plan the inquiry, search (WebSearch/WebFetch), score your own confidence, and keep digging until the answer is well-supported or a hop cap is hit, then emit a cited synthesis. Learns across sessions by storing each research case to memory and reusing prior strategies. Use when a question needs more than one search — comparisons, current-best-practice questions, anything where a single lookup leaves you unsure.

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Authorization Code Flow for web applications using MSAL.NET confidential client to sign in users and access APIs on their behalf

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Benchmark multi-agent coordination systems with experiment design, power analysis, human rating protocols, bootstrap confidence intervals, and reproducible reporting. Use for salvage latency, recovery fidelity, coordination overhead, and protocol comparison studies. NOT for ML model benchmarking, web-product A/B testing, survey design, or general-purpose data science.

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Detects fabricated content, false citations, and unverifiable claims in agent outputs. Uses source verification and consistency checking. Activate on 'detect hallucination', 'fact check', 'verify claims', 'check accuracy', 'find fabrications'. NOT for validation (use dag-output-validator) or confidence scoring (use dag-confidence-scorer).

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。

Validates agent outputs against expected schemas and quality criteria. Ensures outputs meet structural requirements and content standards. Activate on 'validate output', 'output validation', 'schema validation', 'check output', 'output quality'. NOT for confidence scoring (use dag-confidence-scorer) or hallucination detection (use dag-hallucination-detector).

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Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets through Andreessen's actual frameworks — market dominates team and product; the only milestone that matters is product/market fit; bias to build over deliberate. Use when the user says 'andreessen', 'pmarca mode', 'should I build this', 'is there a market', 'are we at product/market fit', 'pmf check', 'pressure-test this idea', 'be brutal about this venture', 'market-first take', or wants a no-disclaimers, no-hedging, confidence-leveled verdict on whether something is worth pursuing. Also provides the 3x5-card + Anti-Todo personal productivity routine. Runs on a fixed anti-sycophancy operating prompt: leads with the strongest counterargument, never validates premises, uses explicit confidence levels, never apologizes for disagreeing. Not for polite brainstorming — this skill exists to tell you the market is dead when it is.

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Detects when Claude is uncertain but presenting answers confidently. Teaches Claude to recognize and communicate uncertainty clearly instead of masking it with confident language.

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Assign confidence scores (0-100) to every claim in a response. Helps users understand which parts are verified facts and which are educated guesses. Use when the user needs to know how much to trust each part of the answer.

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[Code Quality] Use when you need to prove fix correctness with adversarial code proof traces — a skeptic tries to DISPROVE the fix and trace all related paths first, with confidence scoring and stack-trace-style evidence chains, so confidence is earned by surviving attack, not by confirming it works.

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。