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Found 81 Skills
Strategy for creating efficient short-form video prompts. Use when creating filler shots, atmospheric scenes, or quick video clips that don't require full Production Brief methodology. Covers when to go short vs long, format+style upfront rule, and two approaches (Descriptive vs Directive) for compact yet coherent results.
Typst Academic Paper Assistant (supports Chinese and English papers, conference/journal submissions). Domains: Deep Learning, Time Series, Industrial Control, Computer Science. Trigger Words (any module can be called independently): - "compile", "compile", "typst compile" → Compilation Module - "format", "format check", "lint" → Format Check Module - "grammar", "grammar", "proofread", "polish" → Grammar Analysis Module - "long sentence", "long sentence", "simplify", "decompose" → Complex Sentence Analysis Module - "academic tone", "academic expression", "improve writing" → Academic Expression Module - "logic", "coherence", "logic", "cohesion", "methodology", "methodology" → Logical Cohesion & Methodology Depth Module - "translate", "translate", "Chinese to English" → Translation Module - "bib", "bibliography", "bibliography" → Bibliography Module - "deai", "de-AI", "humanize", "reduce AI traces" → De-AI Editing Module - "title", "title", "title optimization", "create title" → Title Optimization Module - "template", "template", "IEEE", "ACM" → Template Configuration Module
Multi-agent distributed context preservation protocol using cryptographic sharding, gossip propagation, and Byzantine fault tolerance to maintain coherent shared memory across dynamic agent networks.
Perform a high-level flow audit of an implementation plan, analyzing phase-to-phase dependencies, data flow consistency, ordering logic, stale artifacts, and risk assessment. Use when asked to 'audit the plan', 'check plan flow', 'review plan dependencies', 'find plan discrepancies', or 'assess plan coherence'. Do NOT use for per-phase template compliance (use /review-plan) or creating plans (use /create-plan).
Generate complete academic survey papers using multi-LLM parallel outline generation, RAG-based subsection writing, citation validation, and local coherence enhancement. Based on AutoSurvey pipeline. Use for writing comprehensive literature surveys.
Groups related git changes into coherent commits and drafts commit messages. Use when the user asks to commit, commit current changes, or create a commit.
Synthesize unstructured thinking into a structured, actionable plan. Use when user provides stream-of-consciousness thoughts, scattered notes, or a brain dump and needs them organized into a coherent plan with goals, actions, and priorities. Trigger phrases: "synthesize", "organize my thoughts", "turn this into a plan", "make sense of this", "structure this", "formalize these notes", "what should I do with all this".
LaTeX Assistant for Chinese Academic Theses (PhD/Master's). Fields: Deep Learning, Time Series, Industrial Control. Trigger Words (call any module independently): - "compile", "compile", "xelatex" → Compilation Module - "structure", "structure", "map" → Structure Mapping Module - "format", "format", "GB/T", "national standard" → National Standard Format Checking Module - "expression", "expression", "polish", "academic expression" → Academic Expression Module - "logic", "coherence", "logic", "cohesion", "methodology", "methodology" → Logical Cohesion & Methodology Depth Module - "long sentence", "long sentence", "split" → Long & Complex Sentence Analysis Module - "bib", "bibliography", "bibliography" → Bibliography Module - "template", "template", "thuthesis", "pkuthss" → Template Detection Module - "deai", "de-AI editing", "humanize", "reduce AI traces" → De-AI Editing Module - "title", "title", "title optimization", "generate title" → Title Optimization Module
Vector database implementation for AI/ML applications, semantic search, and RAG systems. Use when building chatbots, search engines, recommendation systems, or similarity-based retrieval. Covers Qdrant (primary), Pinecone, Milvus, pgvector, Chroma, embedding generation (OpenAI, Voyage, Cohere), chunking strategies, and hybrid search patterns.
Eight-axis judgment code review for the current diff — Correctness, Simplification, Tests, Documentation, Style, Intent, Design/API, Performance (+ Coherence on metadata changes). Five-phase pipeline scope → deterministic tool battery (npx/uvx-preferred, zero-install for the JS + Python majority) → 8 parallel LLM axis reviewers → Haiku validators on sub-80 findings (verbatim rubric, ≥80 threshold) → synthesis with no-silent-drop + Conventional Comments JSONL. Every report closes with "What I did NOT check" (security → /security-review, runtime perf, flaky detection). Opt-in flags `--verify-build`, `--mutation-test`, `--reconcile`, `--apply-safe`. Public-skill posture — zero auto-install, graceful skip on missing native tools.
Use when facing decisions with multiple legitimate perspectives and inherent tensions. Invoke when stakeholders have competing priorities (growth vs. sustainability, speed vs. quality, innovation vs. risk), need to pressure-test ideas from different angles before committing, exploring tradeoffs between incompatible values, synthesizing conflicting expert opinions into coherent strategy, or surfacing assumptions that single-viewpoint analysis would miss.
Map user missions from trigger to value moment, organizing features into coherent paths during PRD v0.4 User Journeys. Triggers on requests to map user journeys, define user flows, describe how users accomplish goals, or when user asks "map user journeys", "define user flows", "user missions", "how do users accomplish X?", "journey mapping", "what steps do users take?", "pain to value flow". Consumes PER- (Persona Definition), FEA- (Feature Value Planning), KPI- (Outcome Definition). Outputs UJ- entries with step flows, pain points, and value moments. Feeds v0.4 Screen Flow Definition.