[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M75NBVAPN8X49N9AJ98ACB9B":3,"skill-same:01M75NBVAPN8X49N9AJ98ACB9B":55},{"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":32,"commitSha":33,"skillDirectory":34,"forksCount":35,"repositoryHtmlUrl":36,"repositoryHomepageUrl":6,"ownerHtmlUrl":37,"ownerBlogUrl":38,"ownerDescription":39,"updatedAt":40,"install":41,"resources":54},"01M75NBVAPN8X49N9AJ98ACB9B","agentic-paper-digest-skill",null,"Fetches and summarizes recent arXiv and Hugging Face papers with Agentic Paper Digest. Use when the user wants a paper digest, a JSON feed of recent papers, or to run the arXiv\u002FHF pipeline.","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\u002Fmatanle51\u002Fagentic-paper-digest\u002FSKILL.md",[],[],"2026-11-12 13:55:43",false,"---\nname: agentic-paper-digest-skill\ndescription: Fetches and summarizes recent arXiv and Hugging Face papers with Agentic Paper Digest. Use when the user wants a paper digest, a JSON feed of recent papers, or to run the arXiv\u002FHF pipeline.\nhomepage: https:\u002F\u002Fgithub.com\u002Fmatanle51\u002Fagentic_paper_digest\ncompatibility: Requires Python 3, network access, and either git or curl\u002Fwget for bootstrap. LLM access via OPENAI_API_KEY or LITELLM_API_KEY (OpenAI-compatible).\nmetadata: {\"clawdbot\":{\"requires\":{\"anyBins\":[\"python3\",\"python\"]}}}\n---\n\n# Agentic Paper Digest\n\n## When to use\n- Fetch a recent paper digest from arXiv and Hugging Face.\n- Produce JSON output for downstream agents.\n- Run a local API server when a polling workflow is needed.\n\n## Prereqs\n- Python 3 and network access.\n- LLM access via `OPENAI_API_KEY` or an OpenAI-compatible provider via `LITELLM_API_BASE` + `LITELLM_API_KEY`.\n- `git` is optional for bootstrap; otherwise `curl`\u002F`wget` (or Python) is used to download the repo.\n\n## Get the code and install\n- Preferred: run the bootstrap helper script. It uses git when available or falls back to a zip download.\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Fbootstrap.sh\"\n```\n\n- Override the clone location by setting `PROJECT_DIR`.\n\n```bash\nPROJECT_DIR=\"$HOME\u002Fagentic_paper_digest\" bash \"{baseDir}\u002Fscripts\u002Fbootstrap.sh\"\n```\n\n## Run (CLI preferred)\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Frun_cli.sh\"\n```\n\n- Pass through CLI flags as needed.\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Frun_cli.sh\" --window-hours 24 --sources arxiv,hf\n```\n\n## Run (API optional)\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Frun_api.sh\"\n```\n\n- Trigger runs and read results.\n\n```bash\ncurl -X POST http:\u002F\u002F127.0.0.1:8000\u002Fapi\u002Frun\ncurl http:\u002F\u002F127.0.0.1:8000\u002Fapi\u002Fstatus\ncurl http:\u002F\u002F127.0.0.1:8000\u002Fapi\u002Fpapers\n```\n\n- Stop the API server if needed.\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Fstop_api.sh\"\n```\n\n## Outputs\n- CLI `--json` prints `run_id`, `seen`, `kept`, `window_start`, and `window_end`.\n- Data store: `data\u002Fpapers.sqlite3` (under `PROJECT_DIR`).\n- API: `POST \u002Fapi\u002Frun`, `GET \u002Fapi\u002Fstatus`, `GET \u002Fapi\u002Fpapers`, `GET\u002FPOST \u002Fapi\u002Ftopics`, `GET\u002FPOST \u002Fapi\u002Fsettings`.\n\n## Configuration\nConfig files live in `PROJECT_DIR\u002Fconfig`. Environment variables can be set in the shell or via a `.env` file. The wrappers here auto-load `.env` from `PROJECT_DIR` (override with `ENV_FILE=\u002Fpath\u002Fto\u002F.env`).\n\n**Environment (.env or exported vars)**\n- `OPENAI_API_KEY`: required for OpenAI models (litellm reads this).\n- `LITELLM_API_BASE`, `LITELLM_API_KEY`: use an OpenAI-compatible proxy\u002Fprovider.\n- `LITELLM_MODEL_RELEVANCE`, `LITELLM_MODEL_SUMMARY`: models for relevance and summarization (summary defaults to relevance model if unset).\n- `LITELLM_TEMPERATURE_RELEVANCE`, `LITELLM_TEMPERATURE_SUMMARY`: lower for more deterministic output.\n- `LITELLM_MAX_RETRIES`: retry count for LLM calls.\n- `LITELLM_DROP_PARAMS=1`: drop unsupported params to avoid provider errors.\n- `WINDOW_HOURS`, `APP_TZ`: recency window and timezone.\n- `ARXIV_CATEGORIES`: comma-separated categories (default includes `cs.CL,cs.AI,cs.LG,stat.ML,cs.CR`).\n- `ARXIV_API_BASE`, `HF_API_BASE`: override source endpoints if needed.\n- `ARXIV_MAX_RESULTS`, `ARXIV_PAGE_SIZE`: arXiv paging limits.\n- `MAX_CANDIDATES_PER_SOURCE`: cap candidates per source before LLM filtering.\n- `FETCH_TIMEOUT_S`, `REQUEST_TIMEOUT_S`: source fetch and per-request timeouts.\n- `ENABLE_PDF_TEXT=1`: include first-page PDF text in summaries; requires `PyMuPDF` (`pip install pymupdf`).\n- `DATA_DIR`: location for `papers.sqlite3`.\n- `CORS_ORIGINS`: comma-separated origins allowed by the API server (UI use).\n- Path overrides: `TOPICS_PATH`, `SETTINGS_PATH`, `AFFILIATION_BOOSTS_PATH`.\n\n**Config files**\n- `config\u002Ftopics.json`: list of topics with `id`, `label`, `description`, `max_per_topic`, and `keywords`. The relevance classifier must output topic IDs exactly as defined here. `max_per_topic` also caps results in `GET \u002Fapi\u002Fpapers` when `apply_topic_caps=1`.\n- `config\u002Fsettings.json`: overrides fetch limits (`arxiv_max_results`, `arxiv_page_size`, `fetch_timeout_s`, `max_candidates_per_source`). Updated via `POST \u002Fapi\u002Fsettings`.\n- `config\u002Faffiliations.json`: list of `{pattern, weight}` boosts applied by substring match over affiliations. Weights add up and are capped at 1.0. Invalid JSON disables boosts, so keep the file strict JSON (no trailing commas).\n\n## Mandatory workflow (follow step-by-step)\n1. **Read existing configuration**:\n   - Load `config\u002Ftopics.json`, `config\u002Fsettings.json`, and `config\u002Faffiliations.json` (if present).\n   - Note current topic IDs, caps, and fetch limits before asking the user to change them.\n2. **Map user intent to configuration (ask only what’s needed)**:\n   - **Topics of interest** → update `config\u002Ftopics.json` (`topics[].id\u002Flabel\u002Fdescription\u002Fkeywords`, `max_per_topic`).  \n     Show current defaults and ask whether to keep or change them.\n   - **Time window (hours)** → set `WINDOW_HOURS` (or pass `--window-hours` to CLI) **only if the user cares**; otherwise keep defaults.\n   - **Search scope** → set `ARXIV_CATEGORIES`, `ARXIV_MAX_RESULTS`, `ARXIV_PAGE_SIZE`, `MAX_CANDIDATES_PER_SOURCE`.  \n     Ask whether to keep defaults and show the current values.\n   - **Model\u002Fprovider** → set `OPENAI_API_KEY` *or* `LITELLM_API_KEY` (+ `LITELLM_API_BASE` if proxy), and set `LITELLM_MODEL_RELEVANCE`\u002F`LITELLM_MODEL_SUMMARY`.\n   - **API UI access** → set `CORS_ORIGINS` only if the user explicitly wants the UI on a different origin.\n   - **Do NOT ask by default**: timezone, quality vs cost, timeouts, PDF text, affiliation biasing, sources list. Use defaults unless the user requests changes.\n3. **Confirm workspace path**: Ask where to clone\u002Frun. Default to `PROJECT_DIR=\"$HOME\u002Fagentic_paper_digest\"` if the user doesn’t care. Never hardcode `\u002FUsers\u002F...` paths.\n4. **Bootstrap the repo**: Run the bootstrap script (unless the repo already exists and the user says to skip).\n5. **Create or verify `.env`**:\n   - If `.env` is missing, create it from `.env.example` (in the repo), then ask the user to fill keys and any requested preferences.\n   - Ensure at least one of `OPENAI_API_KEY` or `LITELLM_API_KEY` is set before running.\n6. **Apply config changes**:\n   - Edit JSON files directly (or use `POST \u002Fapi\u002Ftopics` and `POST \u002Fapi\u002Fsettings` if running the API).\n7. **Run the pipeline**:\n   - Prefer `scripts\u002Frun_cli.sh` for one-off JSON output.\n   - Use `scripts\u002Frun_api.sh` only if the user explicitly asks for UI\u002FAPI access or polling.\n8. **Report results**:\n   - Summarize run stats (`seen`, `kept`, window).\n   - If results are sparse, suggest increasing `WINDOW_HOURS`, `ARXIV_MAX_RESULTS`, or broadening topics.\n\n## Getting good results\n- Keep topics focused and mutually exclusive so the classifier can choose the right IDs.\n- Use a stronger model for summaries than for relevance if quality matters.\n- Increase `WINDOW_HOURS` or `ARXIV_MAX_RESULTS` when results are sparse, or lower them if results are too noisy.\n- Tune `ARXIV_CATEGORIES` to your research domains.\n- Enable PDF text (`ENABLE_PDF_TEXT=1`) when abstracts are too thin.\n- Use modest affiliation weights to bias ranking without swamping relevance.\n\n## Troubleshooting\n- Port 8000 busy: run `bash \"{baseDir}\u002Fscripts\u002Fstop_api.sh\"` or pass `--port` to the API command.\n- Empty results: increase `WINDOW_HOURS` or verify the API key in `.env`.\n- Missing API key errors: export `OPENAI_API_KEY` or `LITELLM_API_KEY` in the shell before running.\n","# Agentic Paper Digest\n\n## When to use\n- Fetch a recent paper digest from arXiv and Hugging Face.\n- Produce JSON output for downstream agents.\n- Run a local API server when a polling workflow is needed.\n\n## Prereqs\n- Python 3 and network access.\n- LLM access via `OPENAI_API_KEY` or an OpenAI-compatible provider via `LITELLM_API_BASE` + `LITELLM_API_KEY`.\n- `git` is optional for bootstrap; otherwise `curl`\u002F`wget` (or Python) is used to download the repo.\n\n## Get the code and install\n- Preferred: run the bootstrap helper script. It uses git when available or falls back to a zip download.\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Fbootstrap.sh\"\n```\n\n- Override the clone location by setting `PROJECT_DIR`.\n\n```bash\nPROJECT_DIR=\"$HOME\u002Fagentic_paper_digest\" bash \"{baseDir}\u002Fscripts\u002Fbootstrap.sh\"\n```\n\n## Run (CLI preferred)\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Frun_cli.sh\"\n```\n\n- Pass through CLI flags as needed.\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Frun_cli.sh\" --window-hours 24 --sources arxiv,hf\n```\n\n## Run (API optional)\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Frun_api.sh\"\n```\n\n- Trigger runs and read results.\n\n```bash\ncurl -X POST http:\u002F\u002F127.0.0.1:8000\u002Fapi\u002Frun\ncurl http:\u002F\u002F127.0.0.1:8000\u002Fapi\u002Fstatus\ncurl http:\u002F\u002F127.0.0.1:8000\u002Fapi\u002Fpapers\n```\n\n- Stop the API server if needed.\n\n```bash\nbash \"{baseDir}\u002Fscripts\u002Fstop_api.sh\"\n```\n\n## Outputs\n- CLI `--json` prints `run_id`, `seen`, `kept`, `window_start`, and `window_end`.\n- Data store: `data\u002Fpapers.sqlite3` (under `PROJECT_DIR`).\n- API: `POST \u002Fapi\u002Frun`, `GET \u002Fapi\u002Fstatus`, `GET \u002Fapi\u002Fpapers`, `GET\u002FPOST \u002Fapi\u002Ftopics`, `GET\u002FPOST \u002Fapi\u002Fsettings`.\n\n## Configuration\nConfig files live in `PROJECT_DIR\u002Fconfig`. Environment variables can be set in the shell or via a `.env` file. The wrappers here auto-load `.env` from `PROJECT_DIR` (override with `ENV_FILE=\u002Fpath\u002Fto\u002F.env`).\n\n**Environment (.env or exported vars)**\n- `OPENAI_API_KEY`: required for OpenAI models (litellm reads this).\n- `LITELLM_API_BASE`, `LITELLM_API_KEY`: use an OpenAI-compatible proxy\u002Fprovider.\n- `LITELLM_MODEL_RELEVANCE`, `LITELLM_MODEL_SUMMARY`: models for relevance and summarization (summary defaults to relevance model if unset).\n- `LITELLM_TEMPERATURE_RELEVANCE`, `LITELLM_TEMPERATURE_SUMMARY`: lower for more deterministic output.\n- `LITELLM_MAX_RETRIES`: retry count for LLM calls.\n- `LITELLM_DROP_PARAMS=1`: drop unsupported params to avoid provider errors.\n- `WINDOW_HOURS`, `APP_TZ`: recency window and timezone.\n- `ARXIV_CATEGORIES`: comma-separated categories (default includes `cs.CL,cs.AI,cs.LG,stat.ML,cs.CR`).\n- `ARXIV_API_BASE`, `HF_API_BASE`: override source endpoints if needed.\n- `ARXIV_MAX_RESULTS`, `ARXIV_PAGE_SIZE`: arXiv paging limits.\n- `MAX_CANDIDATES_PER_SOURCE`: cap candidates per source before LLM filtering.\n- `FETCH_TIMEOUT_S`, `REQUEST_TIMEOUT_S`: source fetch and per-request timeouts.\n- `ENABLE_PDF_TEXT=1`: include first-page PDF text in summaries; requires `PyMuPDF` (`pip install pymupdf`).\n- `DATA_DIR`: location for `papers.sqlite3`.\n- `CORS_ORIGINS`: comma-separated origins allowed by the API server (UI use).\n- Path overrides: `TOPICS_PATH`, `SETTINGS_PATH`, `AFFILIATION_BOOSTS_PATH`.\n\n**Config files**\n- `config\u002Ftopics.json`: list of topics with `id`, `label`, `description`, `max_per_topic`, and `keywords`. The relevance classifier must output topic IDs exactly as defined here. `max_per_topic` also caps results in `GET \u002Fapi\u002Fpapers` when `apply_topic_caps=1`.\n- `config\u002Fsettings.json`: overrides fetch limits (`arxiv_max_results`, `arxiv_page_size`, `fetch_timeout_s`, `max_candidates_per_source`). Updated via `POST \u002Fapi\u002Fsettings`.\n- `config\u002Faffiliations.json`: list of `{pattern, weight}` boosts applied by substring match over affiliations. Weights add up and are capped at 1.0. Invalid JSON disables boosts, so keep the file strict JSON (no trailing commas).\n\n## Mandatory workflow (follow step-by-step)\n1. **Read existing configuration**:\n   - Load `config\u002Ftopics.json`, `config\u002Fsettings.json`, and `config\u002Faffiliations.json` (if present).\n   - Note current topic IDs, caps, and fetch limits before asking the user to change them.\n2. **Map user intent to configuration (ask only what’s needed)**:\n   - **Topics of interest** → update `config\u002Ftopics.json` (`topics[].id\u002Flabel\u002Fdescription\u002Fkeywords`, `max_per_topic`).  \n     Show current defaults and ask whether to keep or change them.\n   - **Time window (hours)** → set `WINDOW_HOURS` (or pass `--window-hours` to CLI) **only if the user cares**; otherwise keep defaults.\n   - **Search scope** → set `ARXIV_CATEGORIES`, `ARXIV_MAX_RESULTS`, `ARXIV_PAGE_SIZE`, `MAX_CANDIDATES_PER_SOURCE`.  \n     Ask whether to keep defaults and show the current values.\n   - **Model\u002Fprovider** → set `OPENAI_API_KEY` *or* `LITELLM_API_KEY` (+ `LITELLM_API_BASE` if proxy), and set `LITELLM_MODEL_RELEVANCE`\u002F`LITELLM_MODEL_SUMMARY`.\n   - **API UI access** → set `CORS_ORIGINS` only if the user explicitly wants the UI on a different origin.\n   - **Do NOT ask by default**: timezone, quality vs cost, timeouts, PDF text, affiliation biasing, sources list. Use defaults unless the user requests changes.\n3. **Confirm workspace path**: Ask where to clone\u002Frun. Default to `PROJECT_DIR=\"$HOME\u002Fagentic_paper_digest\"` if the user doesn’t care. Never hardcode `\u002FUsers\u002F...` paths.\n4. **Bootstrap the repo**: Run the bootstrap script (unless the repo already exists and the user says to skip).\n5. **Create or verify `.env`**:\n   - If `.env` is missing, create it from `.env.example` (in the repo), then ask the user to fill keys and any requested preferences.\n   - Ensure at least one of `OPENAI_API_KEY` or `LITELLM_API_KEY` is set before running.\n6. **Apply config changes**:\n   - Edit JSON files directly (or use `POST \u002Fapi\u002Ftopics` and `POST \u002Fapi\u002Fsettings` if running the API).\n7. **Run the pipeline**:\n   - Prefer `scripts\u002Frun_cli.sh` for one-off JSON output.\n   - Use `scripts\u002Frun_api.sh` only if the user explicitly asks for UI\u002FAPI access or polling.\n8. **Report results**:\n   - Summarize run stats (`seen`, `kept`, window).\n   - If results are sparse, suggest increasing `WINDOW_HOURS`, `ARXIV_MAX_RESULTS`, or broadening topics.\n\n## Getting good results\n- Keep topics focused and mutually exclusive so the classifier can choose the right IDs.\n- Use a stronger model for summaries than for relevance if quality matters.\n- Increase `WINDOW_HOURS` or `ARXIV_MAX_RESULTS` when results are sparse, or lower them if results are too noisy.\n- Tune `ARXIV_CATEGORIES` to your research domains.\n- Enable PDF text (`ENABLE_PDF_TEXT=1`) when abstracts are too thin.\n- Use modest affiliation weights to bias ranking without swamping relevance.\n\n## Troubleshooting\n- Port 8000 busy: run `bash \"{baseDir}\u002Fscripts\u002Fstop_api.sh\"` or pass `--port` to the API command.\n- Empty results: increase `WINDOW_HOURS` or verify the API key in `.env`.\n- Missing API key errors: export `OPENAI_API_KEY` or `LITELLM_API_KEY` in the shell before running.\n",{"name":5,"homepage":24,"metadata":25,"description":7,"compatibility":31},"https:\u002F\u002Fgithub.com\u002Fmatanle51\u002Fagentic_paper_digest",{"clawdbot":26},{"requires":27},{"anyBins":28},[29,30],"python3","python","Requires Python 3, network access, and either git or curl\u002Fwget for bootstrap. LLM access via OPENAI_API_KEY or LITELLM_API_KEY (OpenAI-compatible).","main","f9d3fe7cf9ac8f1ea63a0d96e98e1f510a3814db","skills\u002Fmatanle51\u002Fagentic-paper-digest",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":42,"prompt":52,"zipAvailable":53},[43,46,49],{"tool":44,"command":45},"npx","npx skills add javimosch\u002Fopen-claw-skills --skill agentic-paper-digest-skill",{"tool":47,"command":48},"bunx","bunx skills add javimosch\u002Fopen-claw-skills --skill agentic-paper-digest-skill",{"tool":50,"command":51},"pnpm","pnpm dlx skills add javimosch\u002Fopen-claw-skills --skill agentic-paper-digest-skill","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmatanle51\u002Fagentic-paper-digest\u002FSKILL.md",true,[],[56,64,71,78,85,92],{"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":63},"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":65,"name":66,"nameZh":6,"description":67,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":70,"publishedAt":63},"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":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":77,"publishedAt":63},"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":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":84,"publishedAt":63},"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":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":91,"publishedAt":63},"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":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":63},"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",[],[]]