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"/Users/grapeot/co/knowledge_working/adhoc_jobs/opencode_skill/skills/skill_opencode_agent_to_agent.md", "action": "unchanged (same text as zh pool)", "zh_source": "opencode_skill:skills/skill_opencode_agent_to_agent.md", "bytes": 20069, "tokens": 4387, "description": "OpenCode Agent-to-Agent Skill: Teaches discovery, identity, a plain-text envelope, and receipt classification so an AI agent can contact another session over the existing append path.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 2982, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_opencode_data", "source": "opencode_skill:skills/skill_opencode_data.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/opencode_skill/skills/skill_opencode_data.md", "action": "unchanged (same text as zh pool)", "zh_source": "opencode_skill:skills/skill_opencode_data.md", "bytes": 5914, "tokens": 1275, "description": "OpenCode Data Skill: Use this skill when a user asks you to inspect 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"desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_opencode_submission", "source": "opencode_skill:skills/skill_opencode_submission.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/opencode_skill/skills/skill_opencode_submission.md", "action": "unchanged (same text as zh pool)", "zh_source": "opencode_skill:skills/skill_opencode_submission.md", "bytes": 14965, "tokens": 3239, "description": "OpenCode Submission Skill: Use this skill when a user asks you to submit one prompt to OpenCode, append a follow-up prompt to an existing OpenCode session, run a template-driven batch of OpenCode sessions, or group QA work by slug.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 2054, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_opencode_throughput", "source": "opencode_skill:skills/skill_opencode_throughput.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/opencode_skill/skills/skill_opencode_throughput.md", "action": "unchanged (same text as zh pool)", "zh_source": "opencode_skill:skills/skill_opencode_throughput.md", "bytes": 5760, "tokens": 1408, "description": "OpenCode Throughput Skill: Use this skill when a user asks you to measure how fast their local OpenCode setup actually generates tokens — per provider/model — from the SQLite data OpenCode already records.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 748, "desc_has_cjk": false, "scan_hits": {} }, { "name": "procedural-video-frames", "source": "opus-video-audio-skill:skills/procedural-video-frames/SKILL.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/opus_video_audio_skill/skills/procedural-video-frames/SKILL.md", "action": "unchanged (same text as zh pool)", "zh_source": "opus-video-audio-skill:skills/procedural-video-frames/SKILL.md", "bytes": 21386, "tokens": 5120, "description": "Render short videos as numbered PNG frames from a Python script, then mux them with ffmpeg -- the frame-sequence pipeline, not a DAW and not a text-to-video model. This entry file holds the rules for every render (framing math in angles and the shots that are geometrically impossible, additive linear compositing with one tone map, exposure that must fall as the field of view widens, verification against stale frames and unlooked-at shots, contact sheets, previewing on a phone, ffmpeg assembly) and routes to sub-documents for look development with an independent critic, fine detail across a large zoom (SDFs, level of detail, anti-aliasing, growth), reflections on water, glows/highlights/seams/on-screen text, handing a material layer such as cloth to Blender through a coding agent, narrated explainers (timing the picture to a voice-over, checking TTS takes by transcription, subtitles, illustration plates printed onto the page), explainers that must not read as slides (sets on one sheet with a sliding camera, persistent elements, element-wise arrivals keyed to words, diagrams drawn in the plates' register), and films cut to an existing song (measuring and snapping beats and sung lines, drum-driven glow, one-canvas reveals, a vector-display look, nested zooms and video feedback, lyrics placed where the picture is empty). Use this skill whenever a task involves rendering or animating a short video, reel, short, greeting, explainer, music video or title sequence programmatically; whenever frames are produced by code (numpy, PIL, matplotlib, Blender scripting) and assembled into an mp4; whenever a camera has to push in, pan or reframe over time; whenever compositing a subject over a background with glow, halo, haze or a reflection; or whenever a render looks washed out, too dark, flat, cheap, aliased, or has visible seams and edges, or reads as a slideshow. Reach for it even when the animation sounds trivial (\"just zoom into this image over 10 seconds\"), because the failure modes here -- inverted exposure laws, off-frame geometry, stale-frame review -- are silent and cost whole render passes.", "description_from": "frontmatter", "cjk_chars": 0, "latin_words": 3299, "desc_has_cjk": false, "scan_hits": {} }, { "name": "video-scoring-audio", "source": "opus-video-audio-skill:skills/video-scoring-audio/SKILL.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/opus_video_audio_skill/skills/video-scoring-audio/SKILL.md", "action": "unchanged (same text as zh pool)", "zh_source": "opus-video-audio-skill:skills/video-scoring-audio/SKILL.md", "bytes": 20361, "tokens": 5100, "description": "Compose, render and objectively verify short music cues and sound effects for video, programmatically and without a DAW. Covers the MIDI + fluidsynth + soundfont pipeline for music that has to hit specific timecodes, the Google Lyria generative-music API (endpoint shape, the copyright filter, and its verified inability to honor timing instructions), loudness normalization and tail trimming with ffmpeg, and the measurement techniques an agent must use because it cannot hear audio. Use this skill whenever a task involves scoring or adding music, a soundtrack, a background track, a sting, an SFX bed, or any generated audio to a video, animation, reel, short, or slideshow -- and also whenever audio needs to line up with a storyboard or specific timestamps, when choosing between a generative music API and synthesizing it yourself, when normalizing loudness or fixing clipping in a rendered cue, or when comparing several instrument or arrangement variants, or when laying a music bed and sound effects under a voice-over. Reach for it even if the request sounds simple (\"just add some music to this clip\"), because the timing, clipping and cannot-hear-it failure modes here are silent and ship broken output.", "description_from": "frontmatter", "cjk_chars": 0, "latin_words": 2878, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_outlook", "source": "outlook_skill:skills/skill_outlook.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/outlook_skill/skills/skill_outlook.md", "action": "unchanged (same text as zh pool)", "zh_source": "outlook_skill:skills/skill_outlook.md", "bytes": 13860, "tokens": 3437, "description": "Outlook Skill — Agent Reference: All commands run from the project root.", "description_from": "heading+first_sentence", "cjk_chars": 2, "latin_words": 1612, "desc_has_cjk": false, "scan_hits": { "email": [ "colleague@example.com" ] } }, { "name": "skill_playwright_test", "source": "playwright-test-skill:skills/skill_playwright_test.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/playwright_test_skill/skills/skill_playwright_test.md", "action": "unchanged (same text as zh pool)", "zh_source": "playwright-test-skill:skills/skill_playwright_test.md", "bytes": 9338, "tokens": 2079, "description": "Playwright E2E Test Skill: Help an AI agent turn an unknown or unstable browser flow into a reliable E2E test or a defensible diagnosis by observing the live page step by step before writing automation.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 1364, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_session_keeper", "source": "playwright-test-skill:skills/skill_session_keeper.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/playwright_test_skill/skills/skill_session_keeper.md", "action": "unchanged (same text as zh pool)", "zh_source": "playwright-test-skill:skills/skill_session_keeper.md", "bytes": 8763, "tokens": 1990, "description": "Browser Session Credential 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"heading+first_sentence", "cjk_chars": 0, "latin_words": 1022, "desc_has_cjk": false, "scan_hits": {} }, { "name": "critic_review", "source": "presentation_skill:skills/critic_review.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/presentation_skill/skills/critic_review.md", "action": "unchanged (same text as zh pool)", "zh_source": "presentation_skill:skills/critic_review.md", "bytes": 3375, "tokens": 794, "description": "Critic Review: Abstract goals like making a deck feel \"premium\" and \"clear\" simply cannot be verified by the agent that built it.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 567, "desc_has_cjk": false, "scan_hits": {} }, { "name": "generated_assets", "source": "presentation_skill:skills/generated_assets.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/presentation_skill/skills/generated_assets.md", "action": "unchanged (same text as zh pool)", "zh_source": "presentation_skill:skills/generated_assets.md", "bytes": 5685, "tokens": 1171, "description": "Generated Assets in HTML Decks: Generated assets are local visual components that live inside a DOM-composed slide.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 830, "desc_has_cjk": false, "scan_hits": {} }, { "name": "html_decks", "source": "presentation_skill:skills/html_decks.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/presentation_skill/skills/html_decks.md", "action": "unchanged (same text as zh pool)", "zh_source": "presentation_skill:skills/html_decks.md", "bytes": 17248, "tokens": 4002, "description": "HTML Mode: the Canvas Deck: HTML mode generates the deck as a web page: **one continuous, animated sheet** without slide borders.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 2842, "desc_has_cjk": false, "scan_hits": {} }, { "name": "reference", "source": "presentation_skill:skills/reference.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/presentation_skill/skills/reference.md", "action": "unchanged (same text as zh pool)", "zh_source": "presentation_skill:skills/reference.md", "bytes": 6416, "tokens": 1483, "description": "Presentation Skill — Reference: Detailed contracts and acceptance criteria.", "description_from": "heading+first_sentence", "cjk_chars": 28, "latin_words": 698, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_presentation", "source": "presentation_skill:skills/skill_presentation.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/presentation_skill/skills/skill_presentation.md", "action": "unchanged (same text as zh pool)", "zh_source": "presentation_skill:skills/skill_presentation.md", "bytes": 24283, "tokens": 5112, "description": "Creates presentation slide decks for AI agents. Defaults to image-generated full-slide visuals (outline_visual.md, visual_guideline.md, Reveal.js viewer). Also builds HTML canvas decks: one borderless animated sheet with a camera, written in HTML, CSS and SVG, elements drawn or split on each click, textless plates, and copy drafted by a writing model and fact-checked by the builder. Use for slide decks, keynotes, lectures, teaching decks, speaker notes, or presentation scaffolds.", "description_from": "frontmatter", "cjk_chars": 42, "latin_words": 3418, "desc_has_cjk": false, "scan_hits": {} }, { "name": "speaker_notes", "source": "presentation_skill:skills/speaker_notes.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/presentation_skill/skills/speaker_notes.md", "action": "unchanged (same text as zh pool)", "zh_source": "presentation_skill:skills/speaker_notes.md", "bytes": 13349, "tokens": 2924, "description": "Speaker Notes — Spoken-Delivery Contract: Read this file when creating, expanding, or substantially rewriting speaker notes.", "description_from": "heading+first_sentence", "cjk_chars": 4, "latin_words": 2057, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_resend_email", "source": "resend_email_skill:skills/skill_resend_email.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/resend_email_skill/skills/skill_resend_email.md", "action": "unchanged (same text as zh pool)", "zh_source": "resend_email_skill:skills/skill_resend_email.md", "bytes": 8374, "tokens": 1923, "description": "Resend Email Skill: Use Resend for agent-controlled email sending, received email handling, and team-wide suppression inspection and management.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 732, "desc_has_cjk": false, "scan_hits": { "assigned_secret": [ "API_KEY=replace-with-your-resend-api-key" ], "email": [ "anything@example.resend.app", "no-reply@example.com", "user@example.com" ] } }, { "name": "skill_suppression_analysis", "source": "resend_email_skill:skills/skill_suppression_analysis.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/resend_email_skill/skills/skill_suppression_analysis.md", "action": "unchanged (same text as zh pool)", "zh_source": "resend_email_skill:skills/skill_suppression_analysis.md", "bytes": 13370, "tokens": 2903, "description": "Analyze Resend suppression lists, calculate deliverability metrics and bounce rates, classify bounces and spam complaints, trace originating emails via source IDs, mine post-suppression attempts, discover typo-rescue pairs, and generate actionable operator reports. Load when the user asks for suppression, bounce, complaint, or deliverability analysis.", "description_from": "frontmatter", "cjk_chars": 0, "latin_words": 1368, "desc_has_cjk": false, "scan_hits": { "email": [ "user@example.com" ] } }, { "name": "skill_semantic_search", "source": "semantic-search-skill:skills/skill_semantic_search.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/semantic_search_skill/skills/skill_semantic_search.md", "action": "unchanged (same text as zh pool)", "zh_source": "semantic-search-skill:skills/skill_semantic_search.md", "bytes": 7534, "tokens": 1589, "description": "Indexes local text files with embeddings and searches them by natural-language query through the semantic-search CLI.", "description_from": "frontmatter", "cjk_chars": 0, "latin_words": 1008, "desc_has_cjk": false, "scan_hits": {} }, { "name": "smart_home_skill", "source": "smart_home_skill:skills/smart_home_skill.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/smart_home/skills/smart_home_skill.md", "action": "unchanged (same text as zh pool)", "zh_source": "smart_home_skill:skills/smart_home_skill.md", "bytes": 4434, "tokens": 930, "description": "Smart Home Skill: Operate a local Smart Home Skill service safely through its live OpenAPI schema and private household overlay.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 615, "desc_has_cjk": false, "scan_hits": {} }, { "name": "stripe_skill", "source": "stripe-skill:skills/stripe_skill.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/stripe_skill/skills/stripe_skill.md", "action": "unchanged (same text as zh pool)", "zh_source": "stripe-skill:skills/stripe_skill.md", "bytes": 6160, "tokens": 1263, "description": "Stripe Skill - Agent Reference: Use this skill when a user wants a read-only Stripe finance or sales analysis through the local `stripe_skill` repository.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 645, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_tavily", "source": "tavily-skill:skills/skill_tavily.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/tavily_skill/skills/skill_tavily.md", "action": "unchanged (same text as zh pool)", "zh_source": "tavily-skill:skills/skill_tavily.md", "bytes": 20257, "tokens": 4979, "description": "Runs Tavily-backed web search and URL extraction via python -m tavily_skill with stable JSON envelopes. 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"typefully-twitter-skill:skills/skill_typefully_twitter.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/typefully_twitter_skill/skills/skill_typefully_twitter.md", "action": "unchanged (same text as zh pool)", "zh_source": "typefully-twitter-skill:skills/skill_typefully_twitter.md", "bytes": 10009, "tokens": 2225, "description": "Typefully Twitter Skill — Agent Reference: Use this skill when the user asks an agent to work with X/Twitter through Typefully or analytics.x.com:", "description_from": "heading+first_sentence", "cjk_chars": 11, "latin_words": 1189, "desc_has_cjk": false, "scan_hits": {} }, { "name": "skill_unifi", "source": "unifi-skill:skills/skill_unifi.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/unifi_skill/skills/skill_unifi.md", "action": "unchanged (same text as zh pool)", "zh_source": "unifi-skill:skills/skill_unifi.md", "bytes": 3275, "tokens": 846, "description": "Skill: unifi-skill — read-only UniFi controller observation: Repo: `https://github.com/grapeot/unifi-skill` (master).", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 432, "desc_has_cjk": false, "scan_hits": {} }, { "name": "bestpractice_external_prose", "source": "writing-skill@d1b7864:skills_en/bestpractice_external_prose.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills_en/bestpractice_external_prose.md", "action": "swapped to skills_en", "zh_source": "writing-skill:skills/bestpractice_external_prose.md", "bytes": 18283, "tokens": 3711, "description": "External Prose Diagnosis Vocabulary (Manager Reference): The lesson from `workflow_external_writing.md` is this: writing the same anti-textbook rule into nine different places and then asking the model to self-report \"I scanned it and it's fine\" does not make the rule bind.", "description_from": "heading+first_sentence", "cjk_chars": 14, "latin_words": 2646, "desc_has_cjk": false, "scan_hits": {} }, { "name": "external_prose_lint", "source": "writing-skill@d1b7864:skills_en/external_prose_lint.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills_en/external_prose_lint.md", "action": "swapped to skills_en", "zh_source": "writing-skill:skills/external_prose_lint.md", "bytes": 6785, "tokens": 1654, "description": "External Prose Lint CLI: Run a deterministic hygiene scan on external-facing Markdown drafts: count em dashes, quotes, parenthetical glosses, single-sentence paragraphs, bare URLs, banned lexicon, and more.", "description_from": "heading+first_sentence", "cjk_chars": 2, "latin_words": 900, "desc_has_cjk": false, "scan_hits": {} }, { "name": "reference_writing_thesis_catalog", "source": "writing-skill@d1b7864:skills_en/reference_writing_thesis_catalog.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills_en/reference_writing_thesis_catalog.md", "action": "swapped to skills_en", "zh_source": "writing-skill:skills/reference_writing_thesis_catalog.md", "bytes": 3986, "tokens": 781, "description": "Analytical Perspectives for External Articles (Thesis Catalog): These perspectives distill recurring analytical habits from the author's published work.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 554, "desc_has_cjk": false, "scan_hits": {} }, { "name": "twitter_post_writing", "source": "writing-skill@d1b7864:skills_en/twitter_post_writing.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills_en/twitter_post_writing.md", "action": "swapped to skills_en", "zh_source": "writing-skill:skills/twitter_post_writing.md", "bytes": 11768, "tokens": 2635, "description": "Twitter Distribution Post Writing Workflow (twitter_post_writing): The article's structure is where the writing pipeline invested the most (the writing brief's H2 plan is designed around reader comprehension order).", "description_from": "heading+first_sentence", "cjk_chars": 1, "latin_words": 1490, "desc_has_cjk": false, "scan_hits": {} }, { "name": "workflow_external_writing", "source": "writing-skill@d1b7864:skills_en/workflow_external_writing.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills_en/workflow_external_writing.md", "action": "swapped to skills_en", "zh_source": "writing-skill:skills/workflow_external_writing.md", "bytes": 27754, "tokens": 6345, "description": "External Writing and Drafting Workflow (Operational Spine): This is the operational spine.", "description_from": "heading+first_sentence", "cjk_chars": 651, "latin_words": 3601, "desc_has_cjk": false, "scan_hits": {} }, { "name": "workflow_internal_writing", "source": "writing-skill@d1b7864:skills_en/workflow_internal_writing.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills_en/workflow_internal_writing.md", "action": "swapped to skills_en", "zh_source": "writing-skill:skills/workflow_internal_writing.md", "bytes": 19788, "tokens": 3792, "description": "Internal Writing Workflow: The audience already shares project context.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 2904, "desc_has_cjk": false, "scan_hits": {} }, { "name": "workflow_news_aggregation", "source": "writing-skill@d1b7864:skills_en/workflow_news_aggregation.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills_en/workflow_news_aggregation.md", "action": "skills_en (zh copy was already mostly English)", "zh_source": "writing-skill:skills/workflow_news_aggregation.md", "bytes": 11232, "tokens": 2312, "description": "News Aggregation Writing Workflow (workflow_news_aggregation): A three-operation pipeline for recurring news-briefing production.", "description_from": "heading+first_sentence", "cjk_chars": 13, "latin_words": 1713, "desc_has_cjk": false, "scan_hits": {} }, { "name": "writing_workflows", "source": "writing-skill:skills/writing_workflows.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/writing_skill/skills/writing_workflows.md", "action": "unchanged (same text as zh pool)", "zh_source": "writing-skill:skills/writing_workflows.md", "bytes": 8269, "tokens": 1779, "description": "Skill: Writing Workflows: Two writing workflows, one shared diagnostic vocabulary, and one deterministic lint CLI.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 1128, "desc_has_cjk": false, "scan_hits": {} }, { "name": "zun_music", "source": "zun-music-skill:skills/zun_music.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/zun_music_skill/skills/zun_music.md", "action": "unchanged (same text as zh pool)", "zh_source": "zun-music-skill:skills/zun_music.md", "bytes": 10684, "tokens": 2613, "description": "ZUN-Style Arrangement Skill: Produce a short arrangement, typically one complete phrase of 8 bars, about 15 s, in which a listener both recognises the source tune within the first phrase and hears it as ZUN-style.", "description_from": "heading+first_sentence", "cjk_chars": 13, "latin_words": 1672, "desc_has_cjk": false, "scan_hits": {} }, { "name": "send_email", "source": "context-infrastructure-en@b03c482:rules/skills/send_email.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/context_infrastructure_en/rules/skills/send_email.md", "action": "replacement (English public skill)", "zh_source": null, "bytes": 4346, "tokens": 987, "description": "Skill: Send Email: This skill sends email notifications from a configured workspace mailbox.", "description_from": "heading+first_sentence", "cjk_chars": 0, "latin_words": 469, "desc_has_cjk": false, "scan_hits": { "email": [ "user@example.com" ] } }, { "name": "typefully_post", "source": "context-infrastructure-en@b03c482:rules/skills/typefully_post.md", "path": "/Users/grapeot/co/knowledge_working/adhoc_jobs/context_infrastructure_en/rules/skills/typefully_post.md", "action": "replacement (English public skill)", "zh_source": null, 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