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Found 8,757 Skills
Generates a new image that imitates the style of a reference image while updating content based on user intent. Uses a three-stage pipeline: image annotation (long caption), caption rewriting, and image generation. Use when user asks to "imitate style", "保持这个风格重画", "按这张图风格生成", or "style transfer with new content".
Use this skill when the user says phrases like "get transcript", "transcribe video", "extract script", "help me extract it", "what does this video say", "what did this blogger say", or directly provides a video link requesting content extraction. Even if the user only sends a video link without stating their request, proactively trigger this skill if the context involves benchmark analysis or content extraction. Call video2text.py to obtain the raw transcript, use AI to correct common speech recognition errors, identify the author, and archive it to the benchmark blogger directory. Do NOT trigger for: analyzing viral content patterns (use li-analyzer), recording own topic ideas (use li-recorder), writing own scripts (use li-writer). Use when the user wants to "get transcript", "transcribe video", "extract script", or gives a video link for content extraction. Runs speech-to-text, AI proofreads, and archives to benchmark blogger directory.
Use this skill when the user says "/li", or when the request is related to content creation but the intent is ambiguous and the user is unsure which tool to use. As the main entry point of the li Toolkit, it judges the intent and routes to the corresponding specialized skill. Do NOT trigger: When the user's request clearly matches a specific li-* skill (e.g., "write a script" → li-writer, "deepen a topic" → li-topic), directly trigger the corresponding skill instead of this entry. DO NOT trigger for non-content-creation tasks. Use when the user says "/li" or the intent is ambiguous across multiple li-* tools.
Propose and execute rubric or bucket upgrades. Two modes: **Full rubric bump** (highest-risk action, mandatory 5-step process + cross-model audit) and **--bucket-only lightweight recalibration** (only update bucket boundaries, no changes to rubric formulas). **Phase 2 mandates using cheat-score-blind sub-agent to re-score the calibration pool** — self-scored fallback is not accepted. Trigger phrases: "upgrade rubric"/"bump rubric"/"update formula"/"I want to add a dimension"/"adjust weights"/"recalibrate bucket"/"recalibrate bucket".
Terminal AI agent CLI for Google Gemini and Antigravity models with slash commands, MCP server support, and coding assistance
Pre-drafting context gathering for a demand letter — parties, facts, basis, leverage, BATNA, and privilege filters — written to a structured intake.md the demand-draft skill reads. Use when the user wants to prep a demand letter, run intake before drafting, or capture context for a payment demand, breach/cure notice, cease-and-desist, employment separation, or preservation demand.
Triage a subpoena served on the company — classify it, analyze scope/burden/privilege, cross-check the portfolio, and produce an objections framework, compliance plan, and deadline calendar. Use when the user says "we got a subpoena", "served with a subpoena", or shares a subpoena, CID, or third-party document request to evaluate.
Persist learnings to memory or maintain existing memories. Triggers on "extract learnings", "save this for next time", "remember this pattern", "consolidate memories", "dream", "clean up memories".
Comet Phase 3: Planning and Building. Invoke with /comet-build. Develop a plan and select an execution method (subagent or direct execution) for implementation.
Concept prototype — validate the core idea is worth designing before writing GDDs. Run right after /brainstorm and /setup-engine. Routes to HTML, Engine, or Paper path based on game type. Produces a throwaway build and a PROCEED/PIVOT/KILL verdict.
Three modes. Session mode (default): extracts generalizable lessons from RESEARCH.md and git history at session end; lessons that imply a new or significantly changed skill are handed off to skill-creator. Personalize mode: searches the skills registry via `npx skills find`, reads the target skill(s), checks compatibility and scope overlap against installed skills, interviews the user to understand what they want and what to skip, then creates or improves skills using skill-creator. Registry mode: curates `skillpacks/skill_dictionary.yaml` and `skillpacks/presets/*.yaml` by assessing external packs, judging necessity/compatibility, and recommending subsets. Create mode: designs a brand- new skill from scratch using skill-creator. Never edits SKILL.md directly — all changes go through skill-creator's draft→test→iterate loop, human merges. Trigger phrases: "end session", "extract lessons", "personalize my skills", "integrate this skill", "update skillpack", "find a skill for", "create a skill", "improve skill", "refresh the skillpack registry", "assess this skill pack", "update skill_dictionary.yaml", "update index.yaml".
Comet Phase 2: In-depth Design. Invoke with /comet-design. Produce Design Doc and delta spec through brainstorming.