[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7CC781XTW71M8RVCBJD4MSB":3,"skill-same:01M7CC781XTW71M8RVCBJD4MSB":76},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":28,"commitSha":29,"skillDirectory":30,"forksCount":14,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":33,"install":34,"resources":47},"01M7CC781XTW71M8RVCBJD4MSB","capture",null,"Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says 'capture this', 'brain dump', 'let me dump some ideas', 'I've got a bunch of thoughts', 'here's everything on my mind', 'idea dump', 'let me get this out of my head', 'I need to organize my thoughts', 'here's what I'm thinking', or any variation where someone is unloading a messy stream of ideas, tasks, thoughts, and plans wanting them turned into something coherent. Also trigger when the user pastes or dictates a long, unstructured block of mixed ideas — even without the exact phrase — the intent is the same. Fast-to-action by design: no upfront intake. Output is four sections (Projects\u002FIdeas, Tasks, Connections, How I Can Help) ending with a directive question. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project.","azhri1990\u002Fjarvis-mega-repo","azhri1990","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F281207543?v=4","01M7BMC0WHXB2ZA9SH1PFJDYNS","Nashriq Mokhtar","01M7C4WMQVQ450E0NA99BG7BHA",0,"MIT","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: capture\ndescription: \"Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says 'capture this', 'brain dump', 'let me dump some ideas', 'I've got a bunch of thoughts', 'here's everything on my mind', 'idea dump', 'let me get this out of my head', 'I need to organize my thoughts', 'here's what I'm thinking', or any variation where someone is unloading a messy stream of ideas, tasks, thoughts, and plans wanting them turned into something coherent. Also trigger when the user pastes or dictates a long, unstructured block of mixed ideas — even without the exact phrase — the intent is the same. Fast-to-action by design: no upfront intake. Output is four sections (Projects\u002FIdeas, Tasks, Connections, How I Can Help) ending with a directive question. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project.\"\nlicense: MIT\nmetadata:\n  source_spec: \"megaprompts\u002F05-capture-megaprompt.md\"\n  build_pattern: \"Path B (direct conversion)\"\n  version: 1.0.0\n---\n\n# Capture — Brain-Dump Organizer\n\nA fast-to-action skill for transforming unstructured streams of mixed thoughts, tasks, and ideas into a clean four-section actionable system with zero information loss.\n\n## Invocation Triggers\n\n**Explicit phrases** (any of):\n- \"brain dump\"\n- \"capture this\"\n- \"let me dump some ideas\"\n- \"I've got a bunch of thoughts\"\n- \"here's everything on my mind\"\n- \"idea dump\"\n- \"let me just get this out of my head\"\n- \"I need to organize my thoughts\"\n- \"here's what I'm thinking\"\n\n**Implicit signals** (no phrase, but the intent is unmistakable):\n- User pastes or dictates a long unstructured block of mixed ideas, tasks, plans\n- Multiple unrelated thoughts in one message without organizing framing\n- A wall of bullet-y text covering 3+ unrelated topics\n\nWhen you detect an implicit trigger, run the skill. Do NOT ask \"do you want me to organize this?\" first — the dump itself IS the request.\n\n## Operating Principles (All Five Apply Always)\n\n1. **Capture everything.** Zero loss. Trivial items go in; the user prunes later. Never silently drop something because it \"seemed unimportant\".\n2. **Preserve voice.** If the user said \"build something crazy with AI\", do NOT restate as \"Explore innovative AI-driven solutions.\" Keep the energy and the casual register. See `references\u002Fvoice_preservation.md` for concrete anti-patterns.\n3. **Match output complexity to input.** A 5-task dump does NOT get forced into 4 elaborate sections. See `references\u002Fcomplexity_matching.md` and the Compressed Output Pattern below.\n4. **Be honest about ambiguity.** If you're unsure what something means, flag it. Don't guess silently.\n5. **No action without approval.** The ONLY immediate action is the organization itself. Every offer in Section 4 waits for the user's explicit pick.\n\n## Grill-Me Mid-Organization Clarifier\n\nCapture is fast-to-action by design. **No upfront intake.** The dump is enough — start organizing immediately.\n\nThe grill-me discipline applies as a **single mid-organization clarifying question**, asked **only when** one item in the dump is genuinely ambiguous between *task* and *project*, AND the misclassification would meaningfully change the output:\n\n> **Quick clarification — one item in your dump could go either way. Is [X] a one-shot task or a multi-step project?**\n>\n> *Why I'm asking:* If I guess wrong on a borderline item I either bury a project as a task or inflate a task into a project that doesn't need the structure. One question per dump prevents that.\n\n**Stop condition:** Max 1 clarifying question per dump. After the answer (or if no clarification was needed), deliver the four (or compressed) sections.\n\nIf the dump is unambiguous, skip the clarifier entirely.\n\n**Anti-pattern (do not do this):** asking 3 clarifying questions up front. That breaks the dump-and-organize flow that makes capture useful.\n\n## Section 1: Projects & Ideas\n\nCluster related items into themed projects when natural clustering exists. This section also holds:\n- Standalone creative sparks\n- Half-formed concepts\n- \"What if\" thoughts\n- Embedded decisions (`Decide: X or Y`) and open questions (`Q: ...`) — kept WITHIN the relevant project, NOT extracted into a separate top-level category\n\n**Format per project:**\n\n```\n### {Project name in user's voice}\n\n- {component \u002F sub-idea}\n- {component}\n- Q: {open question this project needs answered}\n- Decide: {decision this project requires}\n```\n\nUse the user's words for the project name. If the user wrote \"ai dating app for ferrets\", do NOT rename it to \"AI-Powered Pet Companion Platform\".\n\n## Section 2: Tasks\n\nFlat, scannable, action-oriented. Includes:\n- Explicit todos\n- Decisions framed as `Decide: ...`\n- Open questions framed as `Resolve: ...`\n\nIf a task belongs to a project from Section 1, append `[Project: X]` to link it — but don't repeat the project's context.\n\n**Format:**\n\n```\n- {task in imperative voice}  [Project: X if related]\n- Decide: {decision}  [Project: X if related]\n- Resolve: {open question}\n- ...\n```\n\n## Section 3: Connections\n\nThis is where the skill earns its keep — and where **fabrication is forbidden**.\n\n**Workflow:**\n\n1. **Inventory the workspace** — Glob for filename patterns matching dump keywords, Grep for content matches, read the top-level directory structure. Use `scripts\u002Fworkspace_inventory.py` to do this deterministically.\n2. **Match dump items to existing content** — files \u002F folders relating to dumped items, prior thinking in documents, in-progress projects with overlap.\n3. **Surface dependencies within the dump** — items that affect each other, themes, ordering implications.\n4. **Be honest about inaccessibility** — if you can't inspect the workspace (no filesystem available, MCP not connected), say so explicitly. Do NOT make up plausible-sounding connections.\n\n**Hard rule:** NEVER fabricate connections. Only surface ones actually found by Glob\u002FGrep\u002FRead. If no real connections exist:\n\n> **Connections:** No connections found — workspace inventory clean.\n\nIf the workspace is inaccessible:\n\n> **Connections:** No workspace accessible from here. If you're running this from Claude Code or have a project with files attached, I can fill this in. Want to share where this work lives?\n\nSee `references\u002Fworkspace_detection.md` for the per-context detection-tactic catalog.\n\n## Section 4: How I Can Help\n\n**Concrete offers, not abstract possibilities.** Every offer specifies what would be produced AND where it would go.\n\n| ✅ Right pattern | ❌ Anti-pattern |\n|---|---|\n| \"I can research Consensus MCP integration patterns and give you 3 options. Output: `docs\u002Fconsensus-options.md`.\" | \"You might want to look into integration approaches.\" |\n| \"I can draft the Q3 launch plan as a 1-pager. Output: chat reply, then `docs\u002Fq3-launch.md` if you want it filed.\" | \"Maybe think about Q3 planning.\" |\n| \"I can scaffold the new auth module with the existing pattern from `src\u002Fusers\u002F`. Output: 4 files in `src\u002Fauth\u002F`.\" | \"We could explore auth options.\" |\n\nEnd with the directive question:\n\n> **Which of these should I tackle?**\n\n## Compressed Output Pattern\n\nWhen the dump has **5 or fewer items** and items are **unrelated** (no natural clustering), drop the 4-section format and use compressed:\n\n```\n## What I heard\n\n- {item}\n- {item}\n- {item}\n- ...\n\n## How I can help\n\n- {concrete offer with what + where}\n- {concrete offer with what + where}\n\nWhich should I tackle?\n```\n\nThe trigger is the `complexity_estimator.py` recommendation OR your judgment when no clusters exist. See `references\u002Fcomplexity_matching.md` for worked examples of when each format applies.\n\n## Workspace Detection Strategy\n\n| Context | Detection method |\n|---|---|\n| Claude Code CLI | Glob for files matching dump keywords; Grep for content matches; read top-level structure. Use `scripts\u002Fworkspace_inventory.py`. |\n| Claude.ai with project | Check project knowledge files for thematic overlap. List file titles; surface matches by keyword. |\n| Connected tools (Notion, Drive, etc.) | Search via MCP if available. |\n| No accessible workspace | State the limitation explicitly; ask user about their setup; do NOT fabricate. |\n\n## Approval Gate\n\nAfter the four (or compressed) sections are delivered:\n\n- **Wait for the user's explicit pick** before doing anything else.\n- If the user says \"go\" without picking a specific offer: honor it, but explicitly note any items you weren't 100% sure about so they can correct.\n- The organization itself is the only auto-action. Every Section 4 offer requires green light.\n\n## Error Handling\n\n| Situation | Behavior |\n|---|---|\n| Workspace inaccessible | State this; skip Section 3 or surface \"no workspace accessible\" + ask about setup |\n| Dump is very short (3-5 items) | Use compressed output; don't force 4 sections |\n| Items are highly ambiguous | Flag in output, ask up to 1 clarifier (or skip clarifier and surface ambiguity in delivery) |\n| Dump contains sensitive info | Acknowledge but don't echo verbatim if user asks for organization without quoting |\n| Conflicting items in the dump | Surface the conflict in Section 1 or 3 explicitly (`Conflict: X says A, Y says B`) |\n| User says \"go\" before approval | Honor it, but explicitly note items you weren't sure about |\n\n## Tooling\n\n| Script | Role |\n|---|---|\n| `scripts\u002Fworkspace_inventory.py` | Glob+Grep helper for Section 3. `python workspace_inventory.py --root . --keywords \"k1,k2\"` returns matches by keyword + folder structure. |\n| `scripts\u002Fdump_classifier.py` | Regex-classifies each dump line into `task` \u002F `decision` \u002F `question` \u002F `idea` \u002F `project-component`. Heuristic — override with judgment. |\n| `scripts\u002Fcomplexity_estimator.py` | Counts items, detects clustering signal, recommends `format=full` or `format=compressed`. |\n\n## References\n\n- `references\u002Fworkspace_detection.md` — context-specific detection tactics (CLI \u002F web \u002F MCP \u002F inaccessible)\n- `references\u002Fvoice_preservation.md` — corporate-speak anti-patterns with concrete examples\n- `references\u002Fcomplexity_matching.md` — compressed vs full output, worked examples\n\n## Anti-Patterns To Reject\n\n- Fabricating workspace connections that weren't actually Glob\u002FGrep-verified\n- Dropping items deemed \"trivial\" — capture everything, let the user prune\n- Corporate-ifying the user's casual language\n- Forcing 4-section structure when input is small (5 simple tasks doesn't need it)\n- Acting on Section-4 offers immediately without approval\n- Splitting decisions\u002Fquestions into a separate top-level category instead of embedding them in the relevant project\n- Vague Section-4 offers (\"you might want to consider…\")\n- Asking 3+ clarifying questions up front (breaks fast-to-action)\n\n---\n\n**Version:** 1.0.0\n**Source spec:** `megaprompts\u002F05-capture-megaprompt.md` (maintainer-local draft spec — gitignored, not present in the public repository)\n**Build pattern:** Path B (direct conversion). Re-grill with `\u002Fcs:grill-with-docs` if drift between spec and implementation surfaces.\n","# Capture — Brain-Dump Organizer\n\nA fast-to-action skill for transforming unstructured streams of mixed thoughts, tasks, and ideas into a clean four-section actionable system with zero information loss.\n\n## Invocation Triggers\n\n**Explicit phrases** (any of):\n- \"brain dump\"\n- \"capture this\"\n- \"let me dump some ideas\"\n- \"I've got a bunch of thoughts\"\n- \"here's everything on my mind\"\n- \"idea dump\"\n- \"let me just get this out of my head\"\n- \"I need to organize my thoughts\"\n- \"here's what I'm thinking\"\n\n**Implicit signals** (no phrase, but the intent is unmistakable):\n- User pastes or dictates a long unstructured block of mixed ideas, tasks, plans\n- Multiple unrelated thoughts in one message without organizing framing\n- A wall of bullet-y text covering 3+ unrelated topics\n\nWhen you detect an implicit trigger, run the skill. Do NOT ask \"do you want me to organize this?\" first — the dump itself IS the request.\n\n## Operating Principles (All Five Apply Always)\n\n1. **Capture everything.** Zero loss. Trivial items go in; the user prunes later. Never silently drop something because it \"seemed unimportant\".\n2. **Preserve voice.** If the user said \"build something crazy with AI\", do NOT restate as \"Explore innovative AI-driven solutions.\" Keep the energy and the casual register. See `references\u002Fvoice_preservation.md` for concrete anti-patterns.\n3. **Match output complexity to input.** A 5-task dump does NOT get forced into 4 elaborate sections. See `references\u002Fcomplexity_matching.md` and the Compressed Output Pattern below.\n4. **Be honest about ambiguity.** If you're unsure what something means, flag it. Don't guess silently.\n5. **No action without approval.** The ONLY immediate action is the organization itself. Every offer in Section 4 waits for the user's explicit pick.\n\n## Grill-Me Mid-Organization Clarifier\n\nCapture is fast-to-action by design. **No upfront intake.** The dump is enough — start organizing immediately.\n\nThe grill-me discipline applies as a **single mid-organization clarifying question**, asked **only when** one item in the dump is genuinely ambiguous between *task* and *project*, AND the misclassification would meaningfully change the output:\n\n> **Quick clarification — one item in your dump could go either way. Is [X] a one-shot task or a multi-step project?**\n>\n> *Why I'm asking:* If I guess wrong on a borderline item I either bury a project as a task or inflate a task into a project that doesn't need the structure. One question per dump prevents that.\n\n**Stop condition:** Max 1 clarifying question per dump. After the answer (or if no clarification was needed), deliver the four (or compressed) sections.\n\nIf the dump is unambiguous, skip the clarifier entirely.\n\n**Anti-pattern (do not do this):** asking 3 clarifying questions up front. That breaks the dump-and-organize flow that makes capture useful.\n\n## Section 1: Projects & Ideas\n\nCluster related items into themed projects when natural clustering exists. This section also holds:\n- Standalone creative sparks\n- Half-formed concepts\n- \"What if\" thoughts\n- Embedded decisions (`Decide: X or Y`) and open questions (`Q: ...`) — kept WITHIN the relevant project, NOT extracted into a separate top-level category\n\n**Format per project:**\n\n```\n### {Project name in user's voice}\n\n- {component \u002F sub-idea}\n- {component}\n- Q: {open question this project needs answered}\n- Decide: {decision this project requires}\n```\n\nUse the user's words for the project name. If the user wrote \"ai dating app for ferrets\", do NOT rename it to \"AI-Powered Pet Companion Platform\".\n\n## Section 2: Tasks\n\nFlat, scannable, action-oriented. Includes:\n- Explicit todos\n- Decisions framed as `Decide: ...`\n- Open questions framed as `Resolve: ...`\n\nIf a task belongs to a project from Section 1, append `[Project: X]` to link it — but don't repeat the project's context.\n\n**Format:**\n\n```\n- {task in imperative voice}  [Project: X if related]\n- Decide: {decision}  [Project: X if related]\n- Resolve: {open question}\n- ...\n```\n\n## Section 3: Connections\n\nThis is where the skill earns its keep — and where **fabrication is forbidden**.\n\n**Workflow:**\n\n1. **Inventory the workspace** — Glob for filename patterns matching dump keywords, Grep for content matches, read the top-level directory structure. Use `scripts\u002Fworkspace_inventory.py` to do this deterministically.\n2. **Match dump items to existing content** — files \u002F folders relating to dumped items, prior thinking in documents, in-progress projects with overlap.\n3. **Surface dependencies within the dump** — items that affect each other, themes, ordering implications.\n4. **Be honest about inaccessibility** — if you can't inspect the workspace (no filesystem available, MCP not connected), say so explicitly. Do NOT make up plausible-sounding connections.\n\n**Hard rule:** NEVER fabricate connections. Only surface ones actually found by Glob\u002FGrep\u002FRead. If no real connections exist:\n\n> **Connections:** No connections found — workspace inventory clean.\n\nIf the workspace is inaccessible:\n\n> **Connections:** No workspace accessible from here. If you're running this from Claude Code or have a project with files attached, I can fill this in. Want to share where this work lives?\n\nSee `references\u002Fworkspace_detection.md` for the per-context detection-tactic catalog.\n\n## Section 4: How I Can Help\n\n**Concrete offers, not abstract possibilities.** Every offer specifies what would be produced AND where it would go.\n\n| ✅ Right pattern | ❌ Anti-pattern |\n|---|---|\n| \"I can research Consensus MCP integration patterns and give you 3 options. Output: `docs\u002Fconsensus-options.md`.\" | \"You might want to look into integration approaches.\" |\n| \"I can draft the Q3 launch plan as a 1-pager. Output: chat reply, then `docs\u002Fq3-launch.md` if you want it filed.\" | \"Maybe think about Q3 planning.\" |\n| \"I can scaffold the new auth module with the existing pattern from `src\u002Fusers\u002F`. Output: 4 files in `src\u002Fauth\u002F`.\" | \"We could explore auth options.\" |\n\nEnd with the directive question:\n\n> **Which of these should I tackle?**\n\n## Compressed Output Pattern\n\nWhen the dump has **5 or fewer items** and items are **unrelated** (no natural clustering), drop the 4-section format and use compressed:\n\n```\n## What I heard\n\n- {item}\n- {item}\n- {item}\n- ...\n\n## How I can help\n\n- {concrete offer with what + where}\n- {concrete offer with what + where}\n\nWhich should I tackle?\n```\n\nThe trigger is the `complexity_estimator.py` recommendation OR your judgment when no clusters exist. See `references\u002Fcomplexity_matching.md` for worked examples of when each format applies.\n\n## Workspace Detection Strategy\n\n| Context | Detection method |\n|---|---|\n| Claude Code CLI | Glob for files matching dump keywords; Grep for content matches; read top-level structure. Use `scripts\u002Fworkspace_inventory.py`. |\n| Claude.ai with project | Check project knowledge files for thematic overlap. List file titles; surface matches by keyword. |\n| Connected tools (Notion, Drive, etc.) | Search via MCP if available. |\n| No accessible workspace | State the limitation explicitly; ask user about their setup; do NOT fabricate. |\n\n## Approval Gate\n\nAfter the four (or compressed) sections are delivered:\n\n- **Wait for the user's explicit pick** before doing anything else.\n- If the user says \"go\" without picking a specific offer: honor it, but explicitly note any items you weren't 100% sure about so they can correct.\n- The organization itself is the only auto-action. Every Section 4 offer requires green light.\n\n## Error Handling\n\n| Situation | Behavior |\n|---|---|\n| Workspace inaccessible | State this; skip Section 3 or surface \"no workspace accessible\" + ask about setup |\n| Dump is very short (3-5 items) | Use compressed output; don't force 4 sections |\n| Items are highly ambiguous | Flag in output, ask up to 1 clarifier (or skip clarifier and surface ambiguity in delivery) |\n| Dump contains sensitive info | Acknowledge but don't echo verbatim if user asks for organization without quoting |\n| Conflicting items in the dump | Surface the conflict in Section 1 or 3 explicitly (`Conflict: X says A, Y says B`) |\n| User says \"go\" before approval | Honor it, but explicitly note items you weren't sure about |\n\n## Tooling\n\n| Script | Role |\n|---|---|\n| `scripts\u002Fworkspace_inventory.py` | Glob+Grep helper for Section 3. `python workspace_inventory.py --root . --keywords \"k1,k2\"` returns matches by keyword + folder structure. |\n| `scripts\u002Fdump_classifier.py` | Regex-classifies each dump line into `task` \u002F `decision` \u002F `question` \u002F `idea` \u002F `project-component`. Heuristic — override with judgment. |\n| `scripts\u002Fcomplexity_estimator.py` | Counts items, detects clustering signal, recommends `format=full` or `format=compressed`. |\n\n## References\n\n- `references\u002Fworkspace_detection.md` — context-specific detection tactics (CLI \u002F web \u002F MCP \u002F inaccessible)\n- `references\u002Fvoice_preservation.md` — corporate-speak anti-patterns with concrete examples\n- `references\u002Fcomplexity_matching.md` — compressed vs full output, worked examples\n\n## Anti-Patterns To Reject\n\n- Fabricating workspace connections that weren't actually Glob\u002FGrep-verified\n- Dropping items deemed \"trivial\" — capture everything, let the user prune\n- Corporate-ifying the user's casual language\n- Forcing 4-section structure when input is small (5 simple tasks doesn't need it)\n- Acting on Section-4 offers immediately without approval\n- Splitting decisions\u002Fquestions into a separate top-level category instead of embedding them in the relevant project\n- Vague Section-4 offers (\"you might want to consider…\")\n- Asking 3+ clarifying questions up front (breaks fast-to-action)\n\n---\n\n**Version:** 1.0.0\n**Source spec:** `megaprompts\u002F05-capture-megaprompt.md` (maintainer-local draft spec — gitignored, not present in the public repository)\n**Build pattern:** Path B (direct conversion). Re-grill with `\u002Fcs:grill-with-docs` if drift between spec and implementation surfaces.\n",{"name":5,"license":15,"metadata":24,"description":7},{"version":25,"source_spec":26,"build_pattern":27},"1.0.0","megaprompts\u002F05-capture-megaprompt.md","Path B (direct conversion)","main","46d43f3edecde97283ac410e9051444d90120cfb","repos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo","https:\u002F\u002Fgithub.com\u002Fazhri1990","2026-10-10 07:58:58",{"source":8,"skillName":5,"commands":35,"prompt":45,"zipAvailable":46},[36,39,42],{"tool":37,"command":38},"npx","npx skills add azhri1990\u002Fjarvis-mega-repo --skill capture",{"tool":40,"command":41},"bunx","bunx skills add azhri1990\u002Fjarvis-mega-repo --skill capture",{"tool":43,"command":44},"pnpm","pnpm dlx skills add azhri1990\u002Fjarvis-mega-repo --skill capture","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002FSKILL.md",true,[48,54,58,62,68,72],{"path":49,"resourceType":50,"resourceTypeDesc":51,"sizeBytes":52,"sourceHtmlUrl":53},"references\u002Fcomplexity_matching.md","REFERENCE","参考文档",7660,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002Freferences\u002Fcomplexity_matching.md",{"path":55,"resourceType":50,"resourceTypeDesc":51,"sizeBytes":56,"sourceHtmlUrl":57},"references\u002Fvoice_preservation.md",4526,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002Freferences\u002Fvoice_preservation.md",{"path":59,"resourceType":50,"resourceTypeDesc":51,"sizeBytes":60,"sourceHtmlUrl":61},"references\u002Fworkspace_detection.md",4937,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002Freferences\u002Fworkspace_detection.md",{"path":63,"resourceType":64,"resourceTypeDesc":65,"sizeBytes":66,"sourceHtmlUrl":67},"scripts\u002Fcomplexity_estimator.py","SCRIPT","脚本",7121,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002Fscripts\u002Fcomplexity_estimator.py",{"path":69,"resourceType":64,"resourceTypeDesc":65,"sizeBytes":70,"sourceHtmlUrl":71},"scripts\u002Fdump_classifier.py",5737,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002Fscripts\u002Fdump_classifier.py",{"path":73,"resourceType":64,"resourceTypeDesc":65,"sizeBytes":74,"sourceHtmlUrl":75},"scripts\u002Fworkspace_inventory.py",7775,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002FJ.A.R.V.I.S\u002Fcomponents\u002Fcore\u002Fclaude-skills\u002F.hermes\u002Fskills\u002Fclaude-skills\u002Fproductivity\u002Fcapture\u002Fscripts\u002Fworkspace_inventory.py",[77,84,91,98,105,112],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":81,"categories":82,"keywords":83,"publishedAt":19},"01M7CYPF9V9EMA4ZXS1TTCMBFH","syllabus","Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fsyllabus\u002Fskills\u002Fsyllabus\u002FSKILL.md",[],[],{"skillNo":85,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":88,"categories":89,"keywords":90,"publishedAt":19},"01M7CYNRJDTQCRF5KGPMBMSB1S","pulse","Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X\u002FTwitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend\u002Fsentiment\u002Fproblems\u002Fopportunities\u002Fcomparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fpulse\u002Fskills\u002Fpulse\u002FSKILL.md",[],[],{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":19},"01M7CYNAVSE84QD7HAWZWTY2FS","patent","Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search \u002F freedom-to-operate \u002F competitive landscape \u002F acquisition diligence \u002F litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",[],[],{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":104,"publishedAt":19},"01M7CYN0CE8P5ZN7WV2X06HKPC","notebooklm","Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio\u002FVideo Overviews, Mind Maps, Reports incl. Briefing Doc\u002FStudy Guide\u002FFAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fnotebooklm\u002Fskills\u002Fnotebooklm\u002FSKILL.md",[],[],{"skillNo":106,"name":107,"nameZh":6,"description":108,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":111,"publishedAt":19},"01M7CYMHZ3QRJ9BKRB859KW8TQ","litreview","Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER \u002F Decomposition \u002F hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5\u002F10\u002F20 queries) controls coverage vs. speed. Output is a 'launching pad' — an orientation guide that lets a researcher dive in confidently, not a finished review. Use when the user starts literature-oriented research (e.g., 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'). Do NOT use for single one-off paper searches wanting a quick list — that's a plain PubMed\u002FOpenAlex (or Consensus) query.","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Flitreview\u002Fskills\u002Flitreview\u002FSKILL.md",[],[],{"skillNo":113,"name":114,"nameZh":6,"description":115,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":116,"categories":117,"keywords":118,"publishedAt":19},"01M7CYM3D8YKV7R6DT4RNJSF0A","grants","NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance\u002FInnovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget\u002Fscope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fgrants\u002Fskills\u002Fgrants\u002FSKILL.md",[],[]]