Results for “sign”

Match a user request to the right skill using trigger matching, project context, and conversation history. Score ambiguity 1–10 and resolve it using context signals or a single clarifying question. Load when project-orchestrator needs to route a request, or when multiple skills could match and the right one is unclear. Also triggers on "which skill should handle this", "route this request", "I'm not sure which skill to use", "disambiguate this", "skill routing". Called by project-orchestrator for request routing. For finding whether a skill exists for a capability, use skill-finder instead.

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 `trend-forecast`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Multi-signal trend forecasting for autonomous agents. Combines prediction market odds, Twitter/X social sentiment, news velocity, and stock market data into a unified trend analysis with confidence scoring. Powered by AIsa — one API key, five data streams. Use when: the user needs X/Twitter research, monitoring, posting, or engagement workflows.

The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.

Writes LinkedIn posts for Heath Barnett in the Built GTM voice. Five post types: Build Log (what I shipped + the receipt + the stack), Lens (GTM opinion — takes a position, no hedging), Scar (a mistake and what it cost), Field (what another operator is shipping), Signal (short forward-looking take). Trigger on "write a post about", "LinkedIn post on", "draft a post", "post idea", "turn this into a LinkedIn post", "help me write something about", or any request to create a LinkedIn post for Heath. Will not generate without a specific receipt or claim — asks for the detail first.

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 `stock-analysis`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to analyze a stock, check a ticker, or compare investments.

Turn "is this account a real fit?" into a stacked verdict. A composite 0-100 fit score built from every signal you have, a breakdown by source, override flags for when a scoring tool is wrong, a channel classification, and a written rationale. Built for reps, marketers, and RevOps, customizable to your CRM and whatever scoring you use. Trigger on "is {account} a real fit?", "score this list against our profile", "find lookalikes to our best customers", "why is the score wrong on {account}?", "validate this prospect list", "what's our coverage in {segment}?", or any account or list qualification.

Talk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less. Use when the user mentions "customer interviews", "validate my idea", "users say they want it but dont buy", "leading questions", "The Mom Test", "customer feedback bias", or "interview script". Also trigger when preparing user research questions, interpreting ambiguous customer feedback, or designing customer discovery processes that avoid false positives. Covers commitment and advancement, avoiding compliments, and extracting signal from noise. For product-market fit, see jobs-to-be-done. For rapid prototype testing, see design-sprint.

Recruit a channel or tech partner and actually activate them, not just sign them. It scores who fits, writes the mutual-value pitch in their terms, builds the enablement that makes them productive, and plans the first co-marketing or co-sell motion so the partnership produces something in the first quarter instead of going dark after the kickoff. Built for B2B partnerships teams, customizable to your CRM and your partner program. Trigger on "recruit a partner", "does this partner fit", "pitch a partnership", "activate a new partner", "partner enablement plan", "first co-marketing motion", or any partner recruiting or activation request.

OWL v5.2 — Pure contrarian. One scanner, one thesis: the crowd is wrong. Monitors crowding across top 30 assets (funding extremity, OI concentration, SM tilt). When crowding persists 4+ hours AND exhaustion signals fire (volume declining, price stalling, RSI divergence), enters AGAINST the crowd to ride the liquidation unwind. 1-2 trades per day max. Re-crowding exit: if the crowd comes back, thesis is dead, exit immediately. DSL High Water Mode (mandatory). The patient predator. v5.2: funding floor lowered from 20% to 12% so the five-factor scoring model actually runs. Added observability logging (top 3 crowding scores per scan cycle).

Restructure any response for an ADHD brain — TL;DR first, ELI16 clarity, short punchy steps, one clear next action, zero walls of text. Use this skill whenever the user says "elihadhd", "adhd mode", "tldr", "eli16", "eli5", "too long", "overwhelmed", "shorter", "just tell me what to do", "break this down", "snap it", "gauntlet", or shows signs of overwhelm (e.g. "wait what", "I'm lost", "too much"). Also use it when the user asks for the simple version, the quick version, or the punchy version of anything — explanations, plans, debugging help, docs, decisions. When in doubt about whether a response is too heavy, use this skill.

Predict genome-wide functional genomics tracks from DNA sequence with Borzoi (Linder 2025) — a sequence-to-function model outputting RNA-seq, CAGE, ATAC, and ChIP coverage across long context, used to score non-coding and regulatory variant effects. Use when predicting functional tracks from a DNA sequence, scoring a non-coding/regulatory variant's effect on expression or chromatin, or doing in-silico mutagenesis of a locus. To LOOK UP a variant's population frequency prefer alterlab-gnomad; for its clinical significance prefer alterlab-clinvar; for protein-structure effects prefer alterlab-alphafold; for single-cell foundation models prefer alterlab-scgpt. Part of the AlterLab Academic Skills suite.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.

Run Mom Test–style customer-discovery interviews to validate or kill an unbuilt idea — generate a non-leading interview guide, conduct or coach the conversations, and synthesize signal vs compliments. Load when the user asks to do customer discovery, run problem interviews, validate an idea with users, run a Mom Test, design an interview guide, or says "talk to customers", "validate the problem", "interview users", "Mom Test this", "did real users want it", "synthesize my interviews", "I just talked to N people". Sub-skill of `venture-exploration`. Hard-bans "would you use this?", solution-pitching, friend/family-only ICP, and treating compliments as validation. Calls `secure-*` before synthesizing any pasted external transcripts.

Query cBioPortal via its keyless REST API for cancer genomics across TCGA, GENIE, MSK-IMPACT and hundreds of studies — somatic mutations, copy-number alterations (GISTIC), mRNA/protein expression, structural variants, and patient-level clinical/survival data. Use when asked how often a gene is mutated/amplified/deleted in a tumor type, to profile oncogenes or tumor suppressors across cancers (pan-cancer alteration frequency), to pull patient-level mutations joined to OS/clinical outcomes, or to validate a cancer target from cohort genomics. For germline variant pathogenicity use alterlab-clinvar; for mutational-signature (SBS) decomposition use alterlab-cosmic; for CRISPR/RNAi gene-dependency use alterlab-depmap; for aggregated target-disease evidence use alterlab-opentargets. Part of the AlterLab Academic Skills suite.

Watch one or more GitHub repositories for new issues, pull requests, comments, PR reviews, and inline diff comments — emits a fresh turn each time something actionable happens. Use when you've opened PRs / issues mimir should know about review activity for, when you want operator-actionable signals for repos mimir maintains, or when you need to track upstream activity on a watched repo. Filters out events authored by mimir's own GitHub identity (set ``MIMIR_GITHUB_SELF_LOGIN``) so the bot doesn't wake itself with its own comments. Companion to the ``pollers`` framework skill (mechanics) and the ``world-scanning`` skill (catalog of *what's worth polling*). Opt-in: copy this directory into ``<home>/skills/github-poller/`` then set the env vars below.

Predicts the highest-impact next action for your project by running a 5-agent meta-DAG pipeline. Gathers project signals automatically (git, recent files, port-daddy, CLAUDE.md), then runs sensemaker → decomposer → skill-selector + premortem → synthesizer. When execution is approved, convert each predicted node into a skillful node prompt using skillful-node-prompt + skillful-subagent-creator, prefer live WinDAGs visualization backed by POST /api/execute and /ws/execution/:id, and fall back to ASCII only when live visualization is unavailable. Activate on: "what should I do", "what's next", "next move", "/next-move", "where should I focus", "what's the highest impact thing right now". NOT for: creating skills, debugging one specific bug, or promising topology-specific runtime behavior the current server cannot execute.

Expert India Digital Personal Data Protection Act, 2023 (DPDPA) compliance advisor. Use this skill whenever a user asks about the DPDPA, DPDP Act, DPDP Rules 2025, India data privacy law, Data Fiduciary obligations, Data Principal rights, Significant Data Fiduciary, Data Protection Board of India, consent under DPDPA, notice requirements, breach notification India, children's data India, cross-border data transfer India, India privacy compliance, DPDPA gap analysis, DPDPA vs GDPR, or any obligation under India's personal data protection framework. Also trigger for: "Section 6 consent", "Section 7 legitimate uses", "Section 9 children's data", "Section 10 SDF", "Section 16 cross-border", "Rule 6 breach notification", "Rule 13 SDF obligations", "Data Protection Board complaint", "verifiable parental consent India", "DPDPA compliance roadmap", or "India privacy law global company".

>- Analyze KiCad projects and PDF schematics: schematics, PCB layouts, Gerbers, footprints, symbols, netlists, and design rules. Reviews designs for bugs, traces nets, cross-references schematic to PCB, extracts BOM data, checks DRC/ERC, DFM, power trees, and regulator circuits. Every finding carries a confidence label and evidence source with trust_summary rollup. Analyzes PDF schematics from dev boards, reference designs, eval kits, and datasheets. Supports KiCad 5–10. Use whenever the user mentions .kicad_sch, .kicad_pcb, .kicad_pro, PCB design review, schematic analysis, PDF schematics, reference designs, Gerber files, DRC/ERC, netlist issues, BOM extraction, signal tracing, power budget, DFM, or wants to understand, debug, compare, or review any hardware design. Also for "check my board", "review before fab", "what's wrong with my schematic", "is this ready to order", "check my...

Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.

Enriches vague, low-detail prompts into structured, agent-optimized XML before execution. INVOKE IMMEDIATELY — before any tool use or file reads — when you detect any of these signals: prompt under 10 words with no file path or error message; vague action verbs with no object ("fix the bug", "make it better", "clean this up", "refactor this", "optimize performance", "improve the UI", "add authentication", "add payments", "add notifications", "build the feature"); CLARIFIER_ADVISORY in your context window; user says "clarify", "help me describe this", "enrich this prompt", "structure my request". Also triggers on: "make this work", "it's broken", "it looks bad", "add X" with no further detail, "implement Y" with no constraints. Do NOT trigger on: prompts ending with ?, prompts containing error messages or stack traces, prompts with specific file paths, prompts already containing acceptance criteria or success metrics.

Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica) as workhorses; optional BYOK MCPs enhance coverage. Use when the user asks for background research, diligence, or meeting prep on a specific entity (e.g., 'prep me for a meeting with [person/company]', 'due diligence on [company]'). Honors sensitivity exclusions for journalism + personal-vetting contexts.

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/Innovation 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/scope-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.

CRITICAL: This skill MUST be used for ALL SSH operations. NEVER use bash 'ssh' or 'scp' commands directly - always use this skill instead. Triggers: ANY mention of 'SSH', 'ssh', 'remote server', 'connect to server', server IPs (e.g., 192.168.x.x, 10.0.x.x), hostnames (e.g., user@host.com, server.example.com), 'login to', 'upload to server', 'download from server', 'deploy', 'run on server', 'check server', 'server status', 'execute remotely', 'bastion host', 'jump host', '跳板机', '服务器', '远程', '连接', '登录', '上传', '下载', '部署', 'transfer between servers', '服务器间传输', '迁移', 'migrate', 'server to server'. If user mentions ANY server operations or provides server connection details, use this skill. This skill provides daemon-based persistent connections, connection pooling, jump host support, server-to-server transfer, automatic error recovery, and significant performance boost. DO NOT use for: local commands, localhost, current directory operations.

When the user needs a comprehensive marketing plan for a client, a company they advise, or their own product. Also use when the user mentions "marketing plan," "growth plan," "GTM plan," "go-to-market plan," "AARRR plan," "90-day marketing plan," "12-month marketing roadmap," "fractional CMO plan," or "fCMO plan." Generates an exhaustive 13-section plan structured by AARRR (Acquisition, Activation, Retention, Referral, Revenue), customized to the client's current budget, team, and stage, mapped to future funding milestones, cross-referenced with the 139-idea marketing-ideas library and an embedded 17-section current-state audit rubric, with a full marketing operations stack showing which skills and MCP/API integrations execute each part. Outputs a Notion-paste-ready markdown document. For positioning and ICP context before planning, see product-marketing. For stage-specific deep work, see onboarding, signup, emails, referrals, pricing.

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.

Reconstruct a product flow, then audit how usable it is — whether it makes sense, where users get confused or stuck, whether the copy and instructions are clear, and where friction causes drop-off. Produces a prioritized, severity-weighted findings report. Works from three inputs: frontend code in a repo, a live running app driven via a browser, or a written flow / spec / screenshots. Use this skill whenever the user asks for a UX review, usability audit, "is this flow confusing", "does this signup/onboarding/checkout make sense", "why are people dropping off", "audit this form", "where's the friction", or hands over a flow and asks whether it's user-friendly. Trigger even on casual phrasings ("is my checkout any good?") — it imposes the structure ad-hoc UX opinions miss. Audits flow usability and friction; for visual polish and interface quality the impeccable audit/critique skills apply instead.

Simulator.Company access-control specialist — who can view/modify/remove/sign/execute an object (actor, form, account, template, tree layer). Use when the user wants to share or unshare an object, grant or revoke permissions, list who has access, or bulk-share. Activate when the user says "share this with", "give access to", "grant permission", "revoke access", "who can see/edit this", "set permissions", "make read-only", "поділись з", "надай доступ", "забери доступ", "хто має доступ", "права доступу", "дай доступ", "открой доступ", "отзови доступ", "кто имеет доступ", "права доступа". Also activate when a tool fails because the caller has NO access to an object — "request access", "I can't see this actor", "access denied", "403", "no permission", "запроси доступ", "немає доступу", "немає прав", "відмовлено в доступі", "запроси доступ", "нет доступа", "доступ запрещён". For the object's own data use the domain skill (`simulator-actors` / `simulator-forms` / `simulator-finance`).

Reverse-engineers a federal RFP we received — given the SOW/PWS and evaluation criteria already in the Theseus KG, reconstructs the CO's hidden decision tree (upstream `sow-pws-builder` 6 scope blocks + 3 intake answers), surfaces hot buttons, ghost language, discriminator hooks, missing-section signals, and CPFF-form / Section-5 / QASP / Key-Personnel traps. USE WHEN the user asks "what scope decisions did the CO already make?", "reverse engineer this RFP", "what hot buttons are hiding in this PWS?", "where are the discriminator hooks?", "did they pick CPFF completion or term form?", "anything suspiciously missing?", or any variant of decoding CO intent. Pulls `requirement`, `deliverable`, `proposal_instruction`, `evaluation_factor`, `clause`, `performance_standard` from the active workspace KG and emits a JSON envelope feeding `proposal-generator`. DO NOT USE FOR proposal prose (`proposal-generator`), pricing (`price-to-win`), clause audit (`compliance-auditor`), or sub SOW (`subcontractor-sow-builder`).

Builds, ships, and debugs native iOS apps: lifecycle, permissions, entitlements, push, widgets, StoreKit, and App Store review. Use when a submission is rejected or a guideline blocks a release; when a permission prompt never appears, or a call fails with a missing-entitlement error; when push, background refresh, or a background upload never runs; when a universal link opens Safari instead of the app; when the app is killed by the watchdog, by jetsam, or with 0xdead10cc, hangs on launch, or crashes only on device; when a widget, Live Activity, or app extension runs out of memory; when purchases, subscriptions, or restore fail; when a privacy manifest, tracking prompt, or data label is required; when layout breaks under Dynamic Type; or when a new iOS release breaks a shipped app. Not for Swift language mechanics (`swift`), IDE, signing and build settings (`xcode`), store listings and submission workflow (`app-store`), or cross-platform apps (`react-native`, `flutter`).

Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.

Audit a landing page or marketing site through one lens: what is the ONE thing this page wants the visitor to do, and does every element on the page move them toward it? Reconstructs who lands on the page and why, spawns visitor-persona agents to react to it cold, maps the belief chain a visitor must climb before acting, inventories CTAs and everything competing with them, then delivers a prioritized cut/move/add/rewrite plan. Use whenever the user asks "what do we want people to do on this page", "is this page converting", "critique this landing page", "why would someone book/buy/sign up here", "audit the funnel on X page", or wants strategic critique of page content and structure (not visual polish). Works from frontend code in a repo, a live URL via browser tools, or pasted copy/screenshots. Judges persuasion and intent-alignment; for flow usability and friction use ux-audit, for visual and aesthetic quality use the impeccable critique/audit skills.

Drafts a federally-defensible SOW or PWS the prime issues to a subcontractor / teaming partner — same FAR 37.102(d) / 37.602 / 16.601(c)(2) / 16.306(d) discipline a contracting officer applies, opposite seat. USE WHEN the user asks to "write a SOW for our sub", "draft a PWS for [Partner]", "build the teaming-partner statement of work", "convert this SOO into a sub SOW", "we need a SOW the sub will sign", or any variant of authoring a downstream work statement. Walks the upstream 3-phase tree (acquisition intake → 6 scope blocks → 14-section assembly), pulls scope from the active Theseus KG (requirements, deliverables, work_scope_items, performance_standards), enforces FAR 37.102(d) "no FTEs in body", emits a chat-only staffing handoff for the prime's cost build, writes Markdown for `renderers` → .docx. DO NOT USE FOR prime proposal prose (`proposal-generator`), reverse-engineering an RFP (`rfp-reverse-engineer`), pricing the sub (`price-to-win`), or clause audit (`compliance-auditor`).

Reviews a product document (PRD, spec, design brief) BEFORE implementation to surface holes — undefined edge cases, missing states, policy gaps — by attacking what the document is SILENT about (things unwritten, and things written only for the happy path). Acts as a strict "sign-off manager," ruling Approve / Conditional / Reject and producing a polite, forwardable question list. Works for planners/PMs (self-review before sharing), engineers (blocking questions before coding), and designers (screen states with no mockup). Use whenever the user wants a spec/PRD/plan/brief checked for readiness or gaps, or says "review this spec", "find holes in this PRD", "poke holes in this", "is this plan good to build?", "can I start implementing this?", "what states/edge cases am I missing?", "what should I ask the PM before coding?", "run devil", or pastes/links a planning document and asks whether it's ready to act on. Do NOT use it to: write or draft a new spec, summarize or translate a document, estimate/break down tic