Results for “skill-discovery”

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.

Access and analyze drug information from the DrugBank database — drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. Use when working with pharmaceutical data, drug discovery research, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task needing detailed drug and drug-target records from DrugBank. Part of the AlterLab Academic Skills suite.

Loads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction. Use when fetching a standardized benchmark dataset, applying scaffold or cold-split evaluation, or sourcing labeled molecules for ADMET, toxicity, or DTI modeling. Sources data, splits, and oracles only — defer molecular featurization (ECFP/fingerprints), model training, and transformers to a molecular-ML skill (e.g. deepchem). Part of the AlterLab Academic Skills suite.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Search command center for web, academic, Tavily, and Perplexity-backed research through one AIsa API key. Use when: the user needs one flagship skill for live search, source discovery, or citation-ready research. Supports fast lookup, answer generation, and deep research reports.

Requires AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `youtube-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. YouTube Search API via AIsa unified endpoint. Search YouTube videos, channels, and playlists with a single AIsa API key — no Google API key or OAuth required. Use this skill when users want to search YouTube content. For other AIsa capabilities (LLM, financial data, Twitter, web search), see the aisa-core skill. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

Make any software agent-native with HKUDS CLI-Anything — four routed modes: install ready-made harnesses via CLI-Hub (cli-hub list/search/info/install/launch), give agents the cli-hub-meta-skill for autonomous discovery, generate a new harness from any codebase/repo via the 7-phase /cli-anything pipeline, or iterate with :refine/:test/:validate; 40+ harnesses, 2,461 tests, Click CLIs with REPL + --json.

Deprecated alias of metabot-browser, kept for one release for backward compatibility. Use when a human asks to connect to or enter Agent Internet, open Agent Internet Browser or Bot Browser, a Bot page, a domain alias, a chain pin, a MetaApp, or a MetaFile — then route the whole request to the metabot-browser skill, which now owns all Browser open, MetaApp discovery, and remix workflows.

Use when a user asks to use, run, delegate, or fulfill a task through a capability that may exist as an online Bot/MetaBot skill-service, especially when no local specialized skill matches. Treat Bot, bot, and MetaBot wording as equivalent and case-insensitive for remote service requests; select from the local cached online service list first, then call the remote service and continue through trace get/watch, optional conversation view opening, and rating closure. Do not use for browse-only service discovery, network source registry management, identity creation/switching, or private chat-only requests.

Comprehensive outbound email strategy skill for cold outreach, email sequences, and multi-channel campaigns. Use when writing cold emails, creating outreach sequences, optimizing response rates, designing follow-up cadences, or building outbound campaigns. Covers prospecting, personalization frameworks, sequence design, subject lines, response handling, compliance, email design, HTML email templates, email layout, email marketing, newsletter design, drip campaigns, email subject lines, email headers, and cold email templates for discovery calls and SDR workflows.

Discovers the core attributes of the current code repository and its projects — languages, frameworks, tooling, and where things live — and writes a concise reference section directly into the project's AGENTS.md or CLAUDE.md for other skills, agents, and hooks to consume. Use when scanning, analyzing, or detecting the project's technology stack, build tools, or repository structure. Does not create or update project documentation — use project-documentation for writing feature or system docs.

Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, returning native rdkit.Chem.Mol objects. Use when running standard cheminformatics pipelines on molecule tables with minimal boilerplate; for low-level control, custom sanitization, or specialized algorithms prefer alterlab-rdkit. Part of the AlterLab Academic Skills suite.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `youtube`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. YouTube SERP Scout for agents. Search top-ranking videos, channels, and trends for content research and competitor tracking. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `web-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Search the web using AIsa Scholar Web endpoint. Returns structured web results with titles, URLs, and snippets. Use when: the user needs web search, research, source discovery, or content extraction.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `scholar-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Search academic papers and scholarly articles via AIsa Scholar endpoint. Supports year range filtering for targeted research. Use when: the user needs web search, research, source discovery, or content extraction.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `openclaw-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API. Use when: the user needs web search, research, source discovery, or content extraction.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `youtube-serp`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Search YouTube SERP results through AISA for video research, channel discovery, trend checking, and competitor tracking. Use when: you need ranked YouTube results for a query, optionally filtered by country or language.

Use when a project's durable context needs to be seeded or refreshed — creating or updating docs/product/context.md (overview + digest + source index + glossary + Know/Don't-Know ledger + design context + technical context) in the target repo; when a project has no context layer yet (Stage-0 setup); when domain terminology is still forming or has drifted; after a meeting, new evidence batch, or scope change that outdates the current context. Also use to ingest new docs/product/input/ batches into the digest. Do not use for repo scaffolding or CI setup, for writing the discovery plan, PRD, or epics (use discovery-plan, prd-writer, epics), or for creating or revising Jobs to be Done — this skill records finished JTBDs by id and marks missing ones TBD; jobs-to-be-done owns minting them.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `smart-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Intelligent hybrid search combining web and academic sources via AIsa Smart Search endpoint. Best when you need both web and scholarly results. Use when: the user needs web search, research, source discovery, or content extraction.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `tavily-extract`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Extract clean, readable content from one or more URLs using Tavily Extract via AIsa API. Useful for reading full articles without visiting the page. Use when: the user needs web search, research, source discovery, or content extraction.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `multi-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Parallel multi-source search combining Web, Scholar, Smart, and Tavily results with confidence scoring and AI synthesis. Best for comprehensive research requiring cross-source validation. Use when: the user needs web search, research, source discovery, or content extraction.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `tavily-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Advanced web search via Tavily through AIsa API. Supports search depth, topic filtering (general/news/finance), time ranges, domain inclusion/exclusion, and LLM-generated answers. Use when: the user needs web search, research, source discovery, or content extraction.

Aspire skill covering the Aspire CLI (start, stop, describe, wait, logs, otel, mcp), AppHost orchestration, service discovery, integrations, MCP server, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application. USE FOR: aspire start, aspire stop, aspire describe, aspire wait, aspire logs, aspire otel, list aspire integrations, debug aspire issues, aspire dashboard, aspire add, aspire mcp tools, aspire docs. DO NOT USE FOR: non-Aspire .NET apps (use dotnet CLI), container-only deployments (use docker/podman).

Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)

Access the AlphaFold DB of 200M+ AI-PREDICTED protein structures — retrieve models by UniProt accession, download PDB/mmCIF files, and analyze prediction confidence metrics (pLDDT, PAE). Use when a UniProt ID needs a computationally predicted 3D structure or when no experimental structure exists, for homology modeling, protein engineering, or structure-based drug discovery; for EXPERIMENTALLY determined structures (X-ray, cryo-EM, NMR) prefer alterlab-pdb, and for protein sequences, annotations, or accession ID mapping prefer alterlab-uniprot instead. Part of the AlterLab Academic Skills suite.

Produces an attorney-ready memo from a corpus of legal documents supplied by the user. Use when a user shows up with a folder, zip, or vault of case documents and asks for a case summary, case evaluation, litigation package, intake memo, matter overview, or "can you summarize this case for me." The skill ingests the corpus into a searchable index, OCRs anything non-searchable, inventories and diagnoses the practice area, loads the appropriate practice-area playbook module(s) (PI/tort, commercial litigation, IP infringement, or user-authored extensions), iteratively searches the corpus across eight core dimensions plus any module-specific dimensions, defers specialized document clusters (depositions, medical records, discovery, liens) to dedicated sibling skills, and synthesizes a cited memo.

Requires node, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `aisa-tavily`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Search the web and extract public page content through AIsa's Tavily-backed API relay. Use when: the user needs open-web research, source discovery, current news lookup, or public URL content extraction. Supports concise result sets, deeper research, and news-focused queries.

Access the RCSB Protein Data Bank (PDB) for EXPERIMENTALLY determined 3D structures (X-ray, cryo-EM, NMR) of proteins and nucleic acids — searching by text, sequence, or structure similarity and downloading coordinates in PDB/mmCIF format with metadata. Use when retrieving a structure by PDB ID, running sequence or structure similarity searches, or obtaining experimental coordinates for structural biology and drug discovery; for AI-PREDICTED structures of proteins lacking experimental data prefer alterlab-alphafold-db, and for protein sequences, annotations, or accession ID mapping prefer alterlab-uniprot instead. Part of the AlterLab Academic Skills suite.

World-class autonomous sales and revenue skill system. Use ANY time the user asks to sell, pitch, prospect, close, negotiate, launch, monetize, build funnels, write outreach, craft proposals, develop pricing, design offers, write sales copy, create email sequences, plan campaigns, position products, handle objections, create playbooks, build pipeline, forecast revenue, develop GTM strategy, optimize conversions, write ad copy, create sales decks, score leads, nurture prospects, upsell, cross-sell, retain customers, write case studies, price products, structure enterprise deals, create battle cards, script discovery calls, build affiliate programs, plan product launches, create webinar funnels, design pricing pages, A/B test offers, analyze unit economics, calculate LTV/CAC, or ANY other sales, revenue, monetization, go-to-market, or commercial growth task. If it involves selling, revenue, deals, pipeline, or commercial strategy — USE THIS SKILL. Trigger aggressively.

Expert Socratic discovery skill for exploring ideas, architecture decisions, and technical design before writing any code. Use this skill — proactively and always first — when requirements are vague, when the user is debating between technical approaches, when the problem is unclear, or when a design decision could have significant architectural consequences. Triggers on: "should we use X or Y", "help me think through", "I'm not sure how to approach this", "what's the best architecture for", "trade-offs between", "design before I code", "let's think through this", "I have an idea", "how should I structure", "help me design", "I want to build X but not sure how", "what approach would you recommend", "is this the right way to". Produces a validated design doc with 2-3 implementation options, trade-offs, and a recommendation. Always use before planning when the approach is not yet locked.

Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Triggers: '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]', or any variation requesting multi-source recency intelligence on a topic. Also use for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.

Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), 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.

Unified skill for content strategy and marketing content strategy: content pillars, editorial calendars, keyword research by buyer stage, positioning, messaging hierarchy, trust-building, GEO/AI search optimization, and ROI measurement. Also handles content briefs, SEO briefs, content outlines for writers, on-page SEO optimization, meta descriptions, title tags, keyword density, content research, source discovery, expert sourcing, and information gathering. Use when planning content strategy, creating content briefs for writers, optimizing existing content for SEO, researching topics and sources, or managing editorial operations. Triggers: content strategy, marketing content strategy, content marketing strategy, content planning, editorial calendar, content pillars, messaging hierarchy, content brief, SEO brief, content outline, keyword research, buyer journey content, GEO optimization, AI search optimization, content ROI, content operations, content roadmap, brand messaging, positioning

Use when asked to fix, build, refactor, review, verify, or release software and the work is non-trivial — including delivering a change request (issue, ticket, or request) from intake through planning, gates, implementation, review, verified PR, and authorized post-merge release. neckbeard routes the change through framing, discovery, design, implementation, review, verification, delivery, and learning — choosing the smallest *safe* intervention, proving it at the real delivery boundary, and leaving an inspectable evidence ledger. For change-request / issue-to-PR work, conditionally loads a 9-phase journey with gates, delivery packet, and lifecycle integration. Composes specialist catalog skills rather than replacing them. Not a persona, not a '10x developer' prompt, not a LOC-minimizer. The journey is not loaded for plain fixes, refactors, or reviews that lack an issue/ticket trajectory.

Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW + g-formula + TMLE triplet, Mendelian randomization, KM/AFT survival, E-value sensitivity, STROBE/TRIPOD reporting) — OR in ML causal inference style (DML, S/T/X/R/DR meta-learners, causal forest, Dragonnet/TARNet/CEVAE, BCF, CATE distribution, policy learning, conformal causal, fairness audit, causal discovery) — OR in distributional / gap-decomposition style (Oaxaca–Blinder `sp.oaxaca`, Kitagawa `sp.kitagawa_decompose`, DiNardo–Fortin–Lemieux `sp.dfl_decompose`, Gelbach `sp.gelbach`, Fairlie `sp.fairlie`, RIF / FFL `sp.rif_decomposition`, all reachable through the `sp.decompose` dispatcher). Also covers exporting mu

Translates stakeholder feature requests into validated outcome statements before any work is committed. Use this skill — proactively and without waiting to be asked — whenever a stakeholder, exec, or customer arrives with a pre-packaged solution: "we need a dashboard", "add a Slack notification", "build an export feature", "create a report", "let's add a filter", "can we just add X". Also triggers for: "how do I push back on this request", "what outcome does this feature solve", "outcome vs output", "outcomes not features", "what are we really trying to achieve", "we're being a feature factory", "I need to reframe this as a problem", "the stakeholder is pushing a specific solution", "discovery before delivery", "assumption testing", "translate this request into an outcome", "ship outcomes not features". Runs the 'One Framework. Four Questions.' protocol (Liatti + Cagan + Torres): Behavior Change → Assumption Test → Cheapest Test → Success Metric. Produces an Outcome Brief with embedded AI prompts ready to pas