「did」の検索結果

When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' 'product update,' 'how do I launch this,' 'site launch,' 'go live,' 'pre-launch QA,' 'launch checklist,' 'GTM plan,' 'we're about to ship,' 'changelog,' 'release notes,' or 'what did we ship this week.' Use this whenever someone is preparing to release something publicly. For ongoing marketing after launch, see marketing-ideas. For the offer being launched (bonuses, guarantees, scarcity, naming), see offers.

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Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"

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Designs and audits PCR and RT-qPCR primers with Primer3, explicit thermodynamic conditions, reference-based off-target amplification searches, and traceable sequence coordinates. Use for designing primer pairs, checking existing primers, exon-junction or isoform-specific assays, variant masking, cloning tails, multiplex compatibility, and interpreting Primer-BLAST results. Includes bounded local in-silico PCR and BLAST screening; distinguishes computational candidates from experimentally validated assays.

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Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.

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Formulates evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Used when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.

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Processes calibrated one-dimensional complex NMR free-induction decays with nmrglue into phased spectra, peak candidates, and signed integration regions. Use for raw 1D NMR processing, ppm-axis verification, apodization, Fourier transformation, manual phasing, baseline correction, or reproducible spectral integration.

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Retrieves and analyzes Cancer Dependency Map (DepMap) release data, including CRISPR Chronos gene effects, cancer model annotations, omics biomarkers, and PRISM drug sensitivity. Supports cancer-selective dependency, co-essentiality, and candidate synthetic-lethality analyses with release-aware identifiers and statistical checks.

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Infers candidate gene regulatory networks from bulk or single-cell expression data using AertsLab Arboreto GRNBoost2 and GENIE3. Use for transcription factor-target association ranking, compatible Dask execution, sparse expression inputs, and network stability checks.

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Applies Arbor Hypothesis Tree Refinement to research artifacts with repeatable evaluators, including model training, agent harnesses, data synthesis and benchmark optimization. Uses persistent hypotheses, isolated experiments, evidence propagation and held-out candidate comparison for multi-experiment research runs. Includes a standard-library state manager and guidance for the RUC-NLPIR Arbor CLI.

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Use when working on, reviewing, or extending GitNexus's CFG/taint/PDG subsystem (the `--pdg` layers), or when reasoning about source→sink data-flow findings. Examples: "How does taint analysis work here?", "Why didn't explain find this flow?", "Add a new sink/source", "Review the interprocedural taint code".

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Advogado criminalista especializado em Maria da Penha, violencia domestica, feminicidio, direito penal brasileiro, medidas protetivas, inquerito policial e acao penal.

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Compares tracked job postings against the candidate profile to identify skill gaps and generate a prioritized learning plan with study resources. Triggers on: /upskill, upskill, skill gaps, what should I learn, learning plan

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Decides what information belongs on a resume or CV, what to leave off and in what order, and audits an existing resume against those norms. Covers every section (contact details, photo, summary, experience, education and GPA, skills, languages, references), candidate situations (new grad, career change, gaps, layoffs, veterans, academic, visa and more) and country and industry norms. Use when the user asks "what should I put on my resume", "what should I leave off", "should I include my photo / GPA / date of birth", "how do I show a gap", "summary or objective?", "how long should my CV be", "CV for a job in Dubai / Germany", "I'm moving to another country, what should I change", "what to put on my resume as a veteran" or "audit / review my resume". Works with pasted text or the Reactive Resume MCP server. For rewriting bullets use resume-bullet-writer; for fitting a resume to one job posting use resume-tailor; for building a new resume as JSON use resume-builder.

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Experimental (preview) Pester skill for migrating classic Should -Be (v5) assertion syntax to the new Should-* (v6) assertions (note the hyphen, no space), e.g. `Should -Be` -> `Should-Be`, `Should -Not -Be` -> `Should-NotBe`. Tracks Pester 6, which is still a release candidate, so this guidance may change; verified against Pester 6.0.0-rc2. Use when converting Pester v5 assertions to Pester v6 Should-* operators, modernizing a Pester test suite, or when a user asks to migrate, convert, or rewrite `Should -...` calls in .Tests.ps1 / PowerShell files.

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Work with OpenViking, the persistent context database behind this agent's memory. Use it whenever the user refers to earlier sessions or shared history ("like last time", "what did we decide"), asks to remember or forget something, shares files, URLs, or repos worth keeping, or when the task needs context this session does not have — even if nobody says the word "memory". Also use it when the user asks where memories are stored: per project, per folder, or shared between repositories. Covers choosing between context search, find, list search, and grep, reading viking:// URIs, and when (not) to write.

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Load relevant OpenViking experience memories via case-linked experience candidates before solving a task.

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Use for the CODE half of a managed Intelligence Channel with Slack or Microsoft Teams: customising the Channel a CLI-scaffolded project already ships, or — for a project the CLI did not generate — writing the Channel declaration, the long-running host, and the awaited activation call. Teams provider setup is in scope, because the CLI or dashboard wizard performs it. Creating a Slack app for the first time is not: if no Slack app exists yet, use setup-slack-channel for the provider half and return here for the code.

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Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access, and builds SIEM detection rules from the event patterns. Use when investigating a suspected cluster compromise, reconstructing what an attacker did through the API server, or writing Kubernetes-specific detection content. Keywords: audit policy, audit log, kube-apiserver, exec into pod, RBAC change, anonymous access, detection rules. Do not use for syscall-level detection inside a running container - use detecting-container-runtime-threats-with-falco. '

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Find people, companies, posts, jobs, service providers and groups on LinkedIn with the Curviate CLI. Covers `search people|companies|posts|jobs|services|groups`, running a pasted LinkedIn search URL directly, the `group` read commands, pagination with `--all`, and the filter traps that silently return unfiltered results. Use when sourcing prospects or candidates, qualifying companies, finding posts or job postings to engage with, or resolving a group.

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Use this skill whenever a developer wants to turn an idea into a complete, production-ready, end-to-end system plan BEFORE writing any code. Trigger on 'plan this system', 'design the architecture for', 'help me blueprint', 'deep plan for X', 'break this idea into components', 'expand into action points', 'full implementation plan', or when the user pastes a project idea wanting architecture, components, pipelines, and file-level execution mapped out. Casual phrasing also triggers: 'help me think this through end-to-end', 'plan before coding'. Also covers living-workspace patterns: self-improving knowledge bases, reflection loops with auditor agents, four-agent teams, schema-as-code, wiki health scoring. **Resume triggers**: 'where did we leave off', 'continue this plan', 'resume my blueprint' - rehydrates state from disk via SESSION.md/NEXT.md/decisions/. Web research is mandatory every invocation.

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Drive LinkedIn Sales Navigator and Recruiter through the Curviate CLI. Covers `sales-nav` (search, profile, message, lead and account lists, save-lead, save-account) and `recruiter` (projects, pipeline, talent-search, save-candidate, project jobs, applicants, message, profile, search), and what can refuse them: the LinkedIn subscription on the connected account, the Curviate seat, and the beta-operations gate. These commands carry no Curviate add-on paywall. Use when working a Sales Navigator or Recruiter seat, or when diagnosing why a premium command failed.

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Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to "search memory", "what did we discuss", "remember when", "find previous conversation", "check history", or before starting work to recall prior decisions.

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Use for Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown requests.

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Distill a reusable skill from anything — a directory, a URL, pasted notes, or what you just did together — or refine an existing skill with new learnings. Use when the user says '/learn', 'learn this', 'turn this into a skill', 'capture this workflow', 'make a skill from <source>', or 'improve/update the <name> skill'. Produces or updates a .claude/skills/<name>/SKILL.md authored to NanoClaw's skill guidelines. (This CREATES or REFINES a skill from a source; it does not install existing skills from a registry.)

日本語の概要は準備中です。原文の説明を表示しています。