[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M75FFAXP2XWM7BFAJS1T3ETD":3,"skill-same:01M75FFAXP2XWM7BFAJS1T3ETD":47},{"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":24,"commitSha":25,"skillDirectory":26,"forksCount":27,"repositoryHtmlUrl":28,"repositoryHomepageUrl":6,"ownerHtmlUrl":29,"ownerBlogUrl":30,"ownerDescription":31,"updatedAt":32,"install":33,"resources":46},"01M75FFAXP2XWM7BFAJS1T3ETD","cross-model-review",null,"Adversarial plan review using two different AI models. Supports static mode (fixed roles) and alternating mode (models swap writer\u002Freviewer each round, fully autonomous). Use when building features touching auth\u002Fpayments\u002Fdata models, or plans >1hr to implement. NOT for simple fixes, research tasks, or quick scripts.","javimosch\u002Fopen-claw-skills","javimosch","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F12900508?v=4","01M6D3F2AS6PV75ET9PZ1QGP8J","Javier Leandro Arancibia","01M75B8NCTAJG9WH5YNZH7C3D8",0,"MIT","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fdon-gbot\u002Fcross-model-review\u002FSKILL.md",[],[],"2026-11-12 13:55:43",false,"---\nname: cross-model-review\ndescription: Adversarial plan review using two different AI models. Supports static mode (fixed roles) and alternating mode (models swap writer\u002Freviewer each round, fully autonomous). Use when building features touching auth\u002Fpayments\u002Fdata models, or plans >1hr to implement. NOT for simple fixes, research tasks, or quick scripts.\n---\n\n# cross-model-review\n\n## Metadata\n```yaml\nname: cross-model-review\nversion: 2.0.0\ndescription: >\n  Adversarial plan review using two different AI models.\n  v2: Alternating mode — models swap writer\u002Freviewer each round.\n  Fully autonomous loop — no human input between rounds.\n  Use when: building features touching auth\u002Fpayments\u002Fdata models,\n  plans that will take >1hr to implement.\n  NOT for: simple one-file fixes, research tasks, quick scripts.\ntriggers:\n  - \"review this plan\"\n  - \"cross review\"\n  - \"challenge this\"\n  - \"is this plan solid?\"\n  - \"adversarial review\"\n```\n\n---\n\n## When to Activate\nActivate this skill when the user:\n- Says any trigger phrase above\n- Shares a plan and asks for adversarial\u002Fsecond-opinion review\n- Asks you to \"sanity check\" a multi-step implementation plan\n\nDo NOT activate for: simple fixes, one-liners, pure research tasks.\n\n---\n\n## Modes\n\n### Static Mode (v1 — backward compatible)\nFixed roles: planner always writes, reviewer always reviews. Requires human to trigger each round.\n\n### Alternating Mode (v2 — recommended)\nModels swap roles each round. Fully autonomous — no human input between rounds.\n\n**Flow:**\n- Round 1: Model A writes the plan. Model B reviews.\n- Round 2: Model B rewrites (based on its own review). Model A reviews.\n- Round 3: Model A rewrites (based on its own review). Model B reviews.\n- ...continues alternating until both agree (reviewer says APPROVED) or max rounds hit.\n\n**Why this works:**\n- Each model must implement its own critique — can't nitpick without owning the fix\n- The other model catches over-engineering or proportionality issues\n- Natural convergence: each round addresses the other's concerns\n\n---\n\n## Autonomous Orchestration (Alternating Mode)\n\nYou (the main agent) run this loop. It's fully autonomous after kickoff.\n\n### Step 1 — Save the plan and init\n\n```bash\nnode review.js init \\\n  --plan \u002Fpath\u002Fto\u002Fplan.md \\\n  --mode alternating \\\n  --model-a \"anthropic\u002Fclaude-opus-4-6\" \\\n  --model-b \"openai-codex\u002Fgpt-5.3-codex\" \\\n  --project-context \"Brief description for reviewer calibration\" \\\n  --out \u002Fhome\u002Fubuntu\u002Fclawd\u002Ftasks\u002Freviews\n```\n\nCaptures workspace path from stdout.\n\n### Step 2 — The autonomous loop\n\n```\nwhile true:\n  step = next-step(workspace)\n\n  if step.action == \"done\":\n    break  # APPROVED!\n\n  if step.action == \"max-rounds\":\n    ask user: override or manual fix\n    break\n\n  if step.action == \"review\":\n    spawn sub-agent with step.model, step.prompt\n    save response to workspace\u002Fround-N-response.json\n    parse-round(workspace, round, response)\n    continue\n\n  if step.action == \"revise\":\n    spawn sub-agent with step.model, step.prompt\n    save output plan to temp file\n    save-plan(workspace, temp file, version)\n    continue\n```\n\n### Step 3 — Finalize\n\nWhen the loop exits with APPROVED:\n```bash\nnode review.js finalize --workspace \u003Cworkspace>\n```\n\nPresent: rounds taken, issues found\u002Fresolved, rubric scores, plan-final.md location.\n\n---\n\n## CLI Reference\n\n```\nCommands:\n  init           Create a review workspace\n  next-step      Get next action for autonomous loop\n  parse-round    Parse a reviewer response, update issue tracker\n  save-plan      Save a revised plan version from writer output\n  finalize       Generate plan-final.md, changelog.md, summary.json\n  status         Print current workspace state\n\ninit options:\n  --plan \u003Cfile>            Path to plan file (required)\n  --mode \u003Cm>               \"static\" (default) or \"alternating\"\n  --model-a \u003Cm>            Model A — writes first (alternating mode, required)\n  --model-b \u003Cm>            Model B — reviews first (alternating mode, required)\n  --reviewer-model \u003Cm>     Reviewer model (static mode, required)\n  --planner-model \u003Cm>      Planner model (static mode, required)\n  --project-context \u003Cs>    Brief project context for reviewer calibration\n  --out \u003Cdir>              Output base dir (default: tasks\u002Freviews)\n  --max-rounds \u003Cn>         Max rounds (default: 5 static, 8 alternating)\n  --token-budget \u003Cn>       Token budget for context (default: 8000)\n\nnext-step options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  Returns JSON: { action, model, round, prompt, planVersion, saveTo }\n  Actions: \"review\", \"revise\", \"done\", \"max-rounds\"\n\nparse-round options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  --round \u003Cn>              Round number (required)\n  --response \u003Cfile>        Path to raw reviewer response (required)\n\nsave-plan options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  --plan \u003Cfile>            Path to revised plan markdown (required)\n  --version \u003Cn>            Plan version number (required)\n\nfinalize options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  --override-reason \u003Cs>    Reason for force-approving with open issues\n  --ci-force               Required in non-TTY mode when overriding\n\nstatus options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n\nExit codes:\n  0   Approved \u002F OK\n  1   Revise \u002F max-rounds\n  2   Error\n```\n\n---\n\n## Detailed Orchestration (for agent implementation)\n\n### Spawning reviewers\n```\nstep = next-step(workspace)  # action: \"review\"\nresponse = sessions_spawn(model=step.model, task=step.prompt, timeout=120s)\n# Save raw response to workspace\u002Fround-{step.round}-response.json\nparse-round(workspace, step.round, response_file)\n```\n\nSystem instruction for reviewer: \"You are a senior engineering reviewer. Output ONLY valid JSON matching the schema. No tool calls. No markdown fences. No preamble.\"\n\n### Spawning writers\n```\nstep = next-step(workspace)  # action: \"revise\"\nrevised_plan = sessions_spawn(model=step.model, task=step.prompt, timeout=300s)\n# Save raw output as temp file\nsave-plan(workspace, temp_file, step.planVersion)\n```\n\nSystem instruction for writer: none needed — the prompt is self-contained.\n\n### Error handling\n- Reviewer timeout\u002Ffailure: retry once, then ask user\n- Writer timeout\u002Ffailure: retry once, then ask user\n- Parse error on review JSON: re-prompt reviewer once with \"Your response was not valid JSON\"\n- Max rounds hit: present status to user, ask for override or manual fix\n\n### Convergence\nThe loop converges when the reviewer says APPROVED with no open CRITICAL\u002FHIGH blockers. The script enforces this — if reviewer says APPROVED but blockers remain, it overrides to REVISE.\n\n---\n\n## Static Mode (v1 — backward compatible)\n\nFor static mode, the original orchestration from v1 still works:\n\n### Step 1 — Init\n```bash\nnode review.js init --plan \u003Cfile> --reviewer-model \u003Cm> --planner-model \u003Cm>\n```\n\n### Step 2 — Manual loop\nFor each round: build reviewer prompt from template, spawn reviewer, parse-round, revise plan yourself, continue.\n\n### Step 3 — Finalize\nSame as alternating mode.\n\n---\n\n## Integration with coding-agent\n\nBefore dispatching any plan to coding-agent that:\n- Touches auth, payments, or data models\n- Has 3+ implementation steps\n- The user hasn't already reviewed adversarially\n\nRun cross-model-review first. Only proceed if exit code 0.\n\n---\n\n## Notes\n- Workspace persists in `tasks\u002Freviews\u002F` — referenceable later\n- `issues.json` tracks full lifecycle of all issues\n- `meta.json` stores mode, models, current round, verdict, needsRevision flag\n- `next-step` is the state machine — always call it to determine what to do\n- Dedup warnings help catch semantic drift across rounds\n- Models must be from different provider families (cross-provider enforcement)\n- `--project-context` is injected into reviewer prompts for calibration\n","# cross-model-review\n\n## Metadata\n```yaml\nname: cross-model-review\nversion: 2.0.0\ndescription: >\n  Adversarial plan review using two different AI models.\n  v2: Alternating mode — models swap writer\u002Freviewer each round.\n  Fully autonomous loop — no human input between rounds.\n  Use when: building features touching auth\u002Fpayments\u002Fdata models,\n  plans that will take >1hr to implement.\n  NOT for: simple one-file fixes, research tasks, quick scripts.\ntriggers:\n  - \"review this plan\"\n  - \"cross review\"\n  - \"challenge this\"\n  - \"is this plan solid?\"\n  - \"adversarial review\"\n```\n\n---\n\n## When to Activate\nActivate this skill when the user:\n- Says any trigger phrase above\n- Shares a plan and asks for adversarial\u002Fsecond-opinion review\n- Asks you to \"sanity check\" a multi-step implementation plan\n\nDo NOT activate for: simple fixes, one-liners, pure research tasks.\n\n---\n\n## Modes\n\n### Static Mode (v1 — backward compatible)\nFixed roles: planner always writes, reviewer always reviews. Requires human to trigger each round.\n\n### Alternating Mode (v2 — recommended)\nModels swap roles each round. Fully autonomous — no human input between rounds.\n\n**Flow:**\n- Round 1: Model A writes the plan. Model B reviews.\n- Round 2: Model B rewrites (based on its own review). Model A reviews.\n- Round 3: Model A rewrites (based on its own review). Model B reviews.\n- ...continues alternating until both agree (reviewer says APPROVED) or max rounds hit.\n\n**Why this works:**\n- Each model must implement its own critique — can't nitpick without owning the fix\n- The other model catches over-engineering or proportionality issues\n- Natural convergence: each round addresses the other's concerns\n\n---\n\n## Autonomous Orchestration (Alternating Mode)\n\nYou (the main agent) run this loop. It's fully autonomous after kickoff.\n\n### Step 1 — Save the plan and init\n\n```bash\nnode review.js init \\\n  --plan \u002Fpath\u002Fto\u002Fplan.md \\\n  --mode alternating \\\n  --model-a \"anthropic\u002Fclaude-opus-4-6\" \\\n  --model-b \"openai-codex\u002Fgpt-5.3-codex\" \\\n  --project-context \"Brief description for reviewer calibration\" \\\n  --out \u002Fhome\u002Fubuntu\u002Fclawd\u002Ftasks\u002Freviews\n```\n\nCaptures workspace path from stdout.\n\n### Step 2 — The autonomous loop\n\n```\nwhile true:\n  step = next-step(workspace)\n\n  if step.action == \"done\":\n    break  # APPROVED!\n\n  if step.action == \"max-rounds\":\n    ask user: override or manual fix\n    break\n\n  if step.action == \"review\":\n    spawn sub-agent with step.model, step.prompt\n    save response to workspace\u002Fround-N-response.json\n    parse-round(workspace, round, response)\n    continue\n\n  if step.action == \"revise\":\n    spawn sub-agent with step.model, step.prompt\n    save output plan to temp file\n    save-plan(workspace, temp file, version)\n    continue\n```\n\n### Step 3 — Finalize\n\nWhen the loop exits with APPROVED:\n```bash\nnode review.js finalize --workspace \u003Cworkspace>\n```\n\nPresent: rounds taken, issues found\u002Fresolved, rubric scores, plan-final.md location.\n\n---\n\n## CLI Reference\n\n```\nCommands:\n  init           Create a review workspace\n  next-step      Get next action for autonomous loop\n  parse-round    Parse a reviewer response, update issue tracker\n  save-plan      Save a revised plan version from writer output\n  finalize       Generate plan-final.md, changelog.md, summary.json\n  status         Print current workspace state\n\ninit options:\n  --plan \u003Cfile>            Path to plan file (required)\n  --mode \u003Cm>               \"static\" (default) or \"alternating\"\n  --model-a \u003Cm>            Model A — writes first (alternating mode, required)\n  --model-b \u003Cm>            Model B — reviews first (alternating mode, required)\n  --reviewer-model \u003Cm>     Reviewer model (static mode, required)\n  --planner-model \u003Cm>      Planner model (static mode, required)\n  --project-context \u003Cs>    Brief project context for reviewer calibration\n  --out \u003Cdir>              Output base dir (default: tasks\u002Freviews)\n  --max-rounds \u003Cn>         Max rounds (default: 5 static, 8 alternating)\n  --token-budget \u003Cn>       Token budget for context (default: 8000)\n\nnext-step options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  Returns JSON: { action, model, round, prompt, planVersion, saveTo }\n  Actions: \"review\", \"revise\", \"done\", \"max-rounds\"\n\nparse-round options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  --round \u003Cn>              Round number (required)\n  --response \u003Cfile>        Path to raw reviewer response (required)\n\nsave-plan options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  --plan \u003Cfile>            Path to revised plan markdown (required)\n  --version \u003Cn>            Plan version number (required)\n\nfinalize options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n  --override-reason \u003Cs>    Reason for force-approving with open issues\n  --ci-force               Required in non-TTY mode when overriding\n\nstatus options:\n  --workspace \u003Cdir>        Path to review workspace (required)\n\nExit codes:\n  0   Approved \u002F OK\n  1   Revise \u002F max-rounds\n  2   Error\n```\n\n---\n\n## Detailed Orchestration (for agent implementation)\n\n### Spawning reviewers\n```\nstep = next-step(workspace)  # action: \"review\"\nresponse = sessions_spawn(model=step.model, task=step.prompt, timeout=120s)\n# Save raw response to workspace\u002Fround-{step.round}-response.json\nparse-round(workspace, step.round, response_file)\n```\n\nSystem instruction for reviewer: \"You are a senior engineering reviewer. Output ONLY valid JSON matching the schema. No tool calls. No markdown fences. No preamble.\"\n\n### Spawning writers\n```\nstep = next-step(workspace)  # action: \"revise\"\nrevised_plan = sessions_spawn(model=step.model, task=step.prompt, timeout=300s)\n# Save raw output as temp file\nsave-plan(workspace, temp_file, step.planVersion)\n```\n\nSystem instruction for writer: none needed — the prompt is self-contained.\n\n### Error handling\n- Reviewer timeout\u002Ffailure: retry once, then ask user\n- Writer timeout\u002Ffailure: retry once, then ask user\n- Parse error on review JSON: re-prompt reviewer once with \"Your response was not valid JSON\"\n- Max rounds hit: present status to user, ask for override or manual fix\n\n### Convergence\nThe loop converges when the reviewer says APPROVED with no open CRITICAL\u002FHIGH blockers. The script enforces this — if reviewer says APPROVED but blockers remain, it overrides to REVISE.\n\n---\n\n## Static Mode (v1 — backward compatible)\n\nFor static mode, the original orchestration from v1 still works:\n\n### Step 1 — Init\n```bash\nnode review.js init --plan \u003Cfile> --reviewer-model \u003Cm> --planner-model \u003Cm>\n```\n\n### Step 2 — Manual loop\nFor each round: build reviewer prompt from template, spawn reviewer, parse-round, revise plan yourself, continue.\n\n### Step 3 — Finalize\nSame as alternating mode.\n\n---\n\n## Integration with coding-agent\n\nBefore dispatching any plan to coding-agent that:\n- Touches auth, payments, or data models\n- Has 3+ implementation steps\n- The user hasn't already reviewed adversarially\n\nRun cross-model-review first. Only proceed if exit code 0.\n\n---\n\n## Notes\n- Workspace persists in `tasks\u002Freviews\u002F` — referenceable later\n- `issues.json` tracks full lifecycle of all issues\n- `meta.json` stores mode, models, current round, verdict, needsRevision flag\n- `next-step` is the state machine — always call it to determine what to do\n- Dedup warnings help catch semantic drift across rounds\n- Models must be from different provider families (cross-provider enforcement)\n- `--project-context` is injected into reviewer prompts for calibration\n",{"name":5,"description":7},"main","f9d3fe7cf9ac8f1ea63a0d96e98e1f510a3814db","skills\u002Fdon-gbot\u002Fcross-model-review",1,"https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills","https:\u002F\u002Fgithub.com\u002Fjavimosch","intrane.fr","Building robust, open-source infrastructure for the commons. AI-leveraged, self-hosted, built to last.","2026-06-07 03:34:58",{"source":8,"skillName":5,"commands":34,"prompt":44,"zipAvailable":45},[35,38,41],{"tool":36,"command":37},"npx","npx skills add javimosch\u002Fopen-claw-skills --skill cross-model-review",{"tool":39,"command":40},"bunx","bunx skills add javimosch\u002Fopen-claw-skills --skill cross-model-review",{"tool":42,"command":43},"pnpm","pnpm dlx skills add javimosch\u002Fopen-claw-skills --skill cross-model-review","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fdon-gbot\u002Fcross-model-review\u002FSKILL.md",true,[],[48,56,63,70,77,84],{"skillNo":49,"name":50,"nameZh":6,"description":51,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":52,"categories":53,"keywords":54,"publishedAt":55},"01M778GGXG2VQ0YF31W2MKGMQZ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[],[],"2026-11-15 14:19:17",{"skillNo":57,"name":58,"nameZh":6,"description":59,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":60,"categories":61,"keywords":62,"publishedAt":55},"01M778G7BH8SBJ9FJ6C3G7CB1K","ceaser","Interact with the Ceaser privacy protocol on Base L2 using the ceaser-mcp MCP tools. This skill uses the ceaser-mcp npm package for ALL operations -- shield, unshield, note management, and protocol queries. All ceaser tool calls use CLI subcommands (npx -y ceaser-mcp \u003Csubcommand>). Ceaser is a privacy-preserving ETH wrapper using Noir\u002FUltraHonk zero-knowledge proofs on Base L2 (chain ID 8453).","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyra-v21\u002Fceaser\u002FSKILL.md",[],[],{"skillNo":64,"name":65,"nameZh":6,"description":66,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":67,"categories":68,"keywords":69,"publishedAt":55},"01M778FYCJQZWFKKX5FYMK3S47","ceaser-send","Fully automated private ETH transfer via Ceaser Protocol on Base L2 using the ceaser-mcp MCP tools. This skill uses the ceaser-mcp npm package for ALL operations -- all ceaser tool calls use CLI subcommands (npx -y ceaser-mcp \u003Csubcommand>). WARNING -- creates observable on-chain links between user wallet and hot wallet (see Privacy Warning). Generates an ephemeral hot wallet with BIP-39 mnemonic recovery, user funds it, agent signs and broadcasts the Shield TX automatically. Exactly one manual step required (funding the hot wallet with ETH). Uses Noir\u002FUltraHonk zero-knowledge proofs.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyra-v21\u002Fceaser-send\u002FSKILL.md",[],[],{"skillNo":71,"name":72,"nameZh":6,"description":73,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":74,"categories":75,"keywords":76,"publishedAt":55},"01M778FQQNSEYA3HJKZBPQ4M9Z","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[],[],{"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":55},"01M778FGVZX7QA2TF9BFMM37FY","moldium","Post and manage content on the Moldium blog platform. Triggered by \"post to Moldium\", \"write a blog post\", \"publish an article\", etc.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyom45\u002Fmoldium\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":55},"01M778F88D8PQ9MQ0KNW2TJ8ZH","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, submit comments, search papers, and import papers. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, submitting paper reviews, searching papers by title, or importing papers from arXiv URLs via API at http:\u002F\u002Fweakaccept.top:8000\u002F.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[],[]]