「reference」の検索結果

Route DoWhy causal inference, graphical causal model, and graph/data workflows to the right sub-skill and bundled references.

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Routes agents working with Axolotl config-driven LLM fine-tuning, datasets, SFT, preference tuning, GRPO/EBFT, model adapters, distributed training, CLI operations, and troubleshooting.

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Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.

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Use when you have a spec, design doc, structured plan, or prompt_plan and need to generate a pipeline Graphviz DOT file for headless autonomous building. The agent reads the spec, extracts build pipeline phases, determines tech stack, asks about human gates and model preferences, generates a validated DOT digraph with rich self-contained prompts, and saves it to the project root. Handles any language or framework.

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Microsoft 365 / Entra ID attack - tenant discovery, user enumeration via OneDrive differential (2026 verified), AADSTS code reference, Smart Lockout math (hard cap 1-2 attempts/user), ROPC validation, Conditional Access mapping. Wiki-first, FIND schema output.

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Athena 全局偏好便利层。直接操作 CC 原生 ~/.claude/settings.json 的 permissions.allow/deny 和全局 CLAUDE.md。

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Build or revise Godot UI from an approved design, separated art, or a visual reference when scene structure, gameplay binding, and runtime visual verification all matter. Use for complete Godot UI integration; use ordinary Godot UI guidance for isolated node or layout questions that do not require an end-to-end visual workflow.

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Use when starting any Blender asset task, planning a production pipeline, coordinating multiple disciplines, or matching a reference photo/concept art. Invoke for game-ready assets, hard surface, environment, character, creature, export, or any multi-skill Blender workflow.

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Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.

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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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Use this skill any time a .pptx or .potx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx or .potx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates (.potx), layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx or .potx filename, regardless of what they plan to do with the content afterward. If a .pptx or .potx file needs to be opened, created, or touched, use this skill.

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AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" request.

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Turn 2+ user reference images into a high-fidelity animated Codex companion using PocketMen's own local stack. Prefer the open-weight Neural Local Studio (FLUX.2 klein 4B; optional Qwen-Image-Edit-2511 Identity-Max) on compatible hardware; otherwise fall back to the deterministic local renderer. Never require hatch-pet or OPENAI_API_KEY for the normal workflow.

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Classifies personal vs non-personal data per GDPR Art. 4(1) definition test with decision tree for borderline cases. References Breyer v Germany CJEU C-582/14 dynamic IP ruling and WP29 Opinion 4/2007. Keywords: personal data, GDPR Art 4, data classification, Breyer ruling, identifiability test, PII.

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Design privacy API patterns including data subject API for DSAR endpoints, consent API for preference management, deletion API with cascading delete orchestration, and audit API for compliance reporting. Provides OpenAPI specifications, error handling, rate limiting, and authentication patterns.

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Assessment of pseudonymization techniques and re-identification risk. Covers tokenization, hashing, encryption-based pseudonymization, and hybrid approaches. Includes re-identification risk scoring using the motivated intruder test, quantitative metrics (marketer, journalist, prosecutor models), and linkage attack resilience evaluation. References ENISA 2019 pseudonymization report.

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Implementation guide for secure multi-party computation enabling privacy-preserving analytics across organizations. Covers secret sharing, garbled circuits, reference frameworks MP-SPDZ and CrypTen, practical deployment patterns, and GDPR alignment for joint controller analytics without revealing individual party inputs.

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Design privacy-preserving analytics systems using differential privacy, k-anonymity, l-diversity, and t-closeness. Covers privacy budget allocation with epsilon tracking, references Google DP library, OpenDP, and Apple PPML. Includes Python differential privacy implementation for GDPR-compliant statistical analysis.

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Guides the creation and review of data processing agreements under GDPR Article 28(3), covering all eight mandatory clauses. References the 2021 Standard Contractual Clauses and provides a compliance checklist for processor contracts. Activate when onboarding processors, reviewing DPAs, or auditing processor compliance. Keywords: DPA, data processing agreement, Article 28, processor, mandatory clauses, standard contractual clauses.

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Implementation guide for CNIL cookie guidelines compliance. References the EUR 150M Google fine and EUR 60M Meta fine. Covers equal prominence accept/reject buttons, cookie wall prohibition, 6-month reconsent intervals, essential cookies exemption, and detailed CNIL Deliberation No. 2020-091 requirements.

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Determines whether a personal data breach triggers notification obligations under GDPR Articles 33 and 34 using structured risk assessment methodology. Covers breach type classification (CIA triad), data sensitivity scoring, volume assessment, identifiability analysis, and consequence severity evaluation. References EDPB Guidelines 01/2021 with 18 breach scenarios. Keywords: breach risk assessment, GDPR, Article 33, Article 34, EDPB, notification threshold.

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Designing and implementing CNIL-compliant cookie consent banners for French and EU audiences. References the EUR 100M Google LLC fine and EUR 150M Meta Platforms fine for non-compliant cookie practices. Covers equal prominence, reject-all buttons, cookie walls prohibition, and 6-month reconsent cycles.

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Manages privacy compliance for employee background checks including criminal record processing under Art. 10 GDPR, DBS checks (UK), national law variations, and reference verification. Applies proportionality and data minimisation to pre-employment screening, defines retention limits, and addresses role-based necessity assessments. Keywords: background check, criminal record, Art. 10, DBS, pre-employment screening, vetting, data minimisation, proportionality.

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