error-check
Identifies severe factual errors in content. Use when asked to fact-check documentation for major inaccuracies.
Identifies severe factual errors in content. Use when asked to fact-check documentation for major inaccuracies.
Aggressively rewrites dense technical prose to maximize Flesch Reading Ease scores. Simplifies vocabulary, shortens sentences, splits paragraphs, and removes filler — without losing technical accuracy.
Reviews Azure content for security vulnerabilities and best practice gaps. Use when asked to perform a security review of documentation.
Search, rank, and help download medical imaging datasets with a structured local index of 1100+ records from Project-Imaging-X. Use when the user asks for dataset discovery, open-only filtering, platform-specific search, or download guidance across modalities, anatomies, diseases, and tasks.
Editorial standards, page conventions, citation system, and talk page structure for whoami.wiki. Use when writing, reviewing, or editing wiki pages.
Guide for creating new Claude Code skills. Use when you need to create a new skill to package expertise or workflow into a reusable capability that Claude can automatically invoke.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Workflow and tools for adding new entries from temp.md to the section files. Includes legend format, section reference, code tools, and common pitfalls. USE FOR: Adding new resources to the knowledge base. DO NOT USE FOR: Editing existing entries or restructuring sections.
Workflow for updating the LLM landscape paper pool (section/x_llm_papers.md) using fetch_llm_papers.py. Covers full re-fetch, resume from checkpoint, and adding new topics. USE FOR: Refreshing citation counts, expanding topic coverage. DO NOT USE FOR: Adding hand-curated entries to section files (use add-new-entry), updating RAG/Agent citation sections in best_practices.md (use update-cite-count).
Build a 2+ level taxonomy (`outline/taxonomy.yml`) from a core paper set and scope constraints, with short descriptions per node. **Trigger**: taxonomy, taxonomy builder, 分类, 主题树, taxonomy.yml. **Use when**: survey/snapshot 的结构阶段(NO PROSE),已有 `papers/core_set.csv`,需要生成可映射且读者友好的主题结构。 **Skip if**: 已经有批准过且可映射的 taxonomy(不要无意义重构)。 **Network**: none. **Guardrail**: 避免泛化占位桶;保持 2+ 层且每节点有具体描述。
Evidence self-loop for surveys: read evidence bindings + evidence packs, then write an actionable upstream TODO plan (which stage/skill to fix) before writing more prose. Writes `output/EVIDENCE_SELFLOOP_TODO.md`. **Trigger**: evidence self-loop, evidence loop, evidence gaps, binding gaps, blocking_missing, 证据自循环, 证据缺口回路. **Use when**: C4 outputs exist (`outline/evidence_bindings.jsonl`, `outline/evidence_drafts.jsonl`) but writing looks hollow or C5 is BLOCKED due to thin evidence. **Skip if**: you are still pre-C3 (no notes/evidence bank yet), or you want to draft anyway and accept a lower evidence bar. **Network**: none. **Guardrail**: analysis-only; do not edit evidence/writing artifacts; do not invent facts/citations; only write the TODO report.
Normalize terminology across a draft (canonical terms + synonym policy) without changing citations or meaning. **Trigger**: terminology, glossary, consistent terms, 术语统一, 统一叫法, 术语表. **Use when**: the draft has concept drift (same thing called 2–3 names) or global-review flags terminology inconsistency. **Skip if**: you are still changing the outline/taxonomy heavily (do that first). **Network**: none. **Guardrail**: do not add/remove citation keys; do not introduce new claims; avoid moving citations across subsections.
Remove repeated boilerplate across sections (methodology disclaimers, generic transitions, repeated summaries) while preserving citations and meaning. **Trigger**: redundancy, repetition, boilerplate removal, 去重复, 去套话, 合并重复段落. **Use when**: the draft feels rigid because the same paragraph shape and disclaimer repeats across many subsections. **Skip if**: you are still drafting major missing sections (finish drafting first). **Network**: none. **Guardrail**: do not add/remove citation keys; do not move citations across subsections; do not delete subsection-specific content.
Refresh stale or drifting learnings and pattern docs in docs/solutions/ by reviewing, updating, consolidating, replacing, or deleting them against the current codebase. Use after refactors, migrations, dependency upgrades, or when a retrieved learning feels outdated or wrong. Also use when reviewing docs/solutions/ for accuracy, when a recently solved problem contradicts an existing learning, when pattern docs no longer reflect current code, or when multiple docs seem to cover the same topic and might benefit from consolidation.
Document a recently solved problem to compound your team's knowledge
Bind papers to chapter-level sections first, writing `outline/section_bindings.jsonl` and `outline/section_binding_report.md`. **Trigger**: section bindings, chapter bindings, section-first binding, 章节绑定, 章级绑定. **Use when**: survey structure should measure chapter saturation before stable H3 decomposition. **Skip if**: chapter skeleton is missing or the bindings are already refined. **Network**: none. **Guardrail**: NO PROSE; do not invent papers; produce auditable PASS/BLOCKED/REROUTE signals.
Analyze and optimize a WordPress site's category taxonomy. Exports all posts, uses AI to suggest an improved category structure — merging duplicates, retiring dead categories, creating missing ones, writing descriptions, and re-categorizing posts. Run this when the user wants to clean up or improve their categories.
Import NotebookLM notebooks into your Obsidian vault as linked knowledge graphs. Sources become wikilink-able files, Q&A answers get citations resolved to [[wikilinks]] with passage-level deep links. Use when user says "notebooklm import", "import notebook", "notebooklm sources", or wants to import NotebookLM data into vault files.
Turn expert podcasts into personalized protocols with cited experiments. Load 300 episodes from terminal, run an expert-informed interview, build experiments in your Obsidian morning routine. Use when user says "notebooklm", "load channel", "expert interview", "notebooklm ask", "health protocol", or wants to turn expert content into actionable experiments.
Magazine-style layout principles for curated editorial digests. Defines layout sections, visual anti-patterns, and narrative prioritization rules. Pairs with ui-generator for technical constraints.
Troubleshoot systematically using the Scientific Method. Use when debugging crashes, tracing errors, diagnosing unexpected behavior, or investigating exceptions. (triggers: debug, fix bug, crash, error, exception, troubleshooting)
Troubleshoot systematically using the Scientific Method. Use when debugging crashes, tracing errors, diagnosing unexpected behavior, or investigating exceptions. (triggers: debug, fix bug, crash, error, exception, troubleshooting)