「candidates」の検索結果

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.

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。

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.

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。

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

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。

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.

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。

WorkorAI talent marketplace skill: candidate job search and employer hiring with white-box match explanations via the WorkorAI MCP server (https://workorai.com/mcp). Use when the user asks to find a job, apply to jobs, respond to employer invitations, or when an employer wants to post jobs, search and evaluate candidates, invite them, and review applicants.

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。

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.

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。

Takes a pile of applications and turns it into a ranked shortlist, scored only against the job's stated rubric, with drafted replies to every candidate, scheduled interviews, and an onboarding checklist for whoever gets hired. Picks up where job-post-builder leaves off and carries the funnel through to first day, including the payroll setup handoff. Runs on Gmail and Google Calendar, deepens with Gusto, DocuSign, and Drive or M365, and works entirely from uploaded resumes with drafted replies the owner sends by hand. Use this whenever the owner has applicants to deal with — including phrasings like "I've got 40 resumes and no time," "who should I interview," "screen these applications," "help me narrow this down," "set up interviews for the top three," or "I need to tell the rest no." Reach for it when the owner mentions applicants, resumes, candidates, or being buried in a hiring inbox.

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。

Create structured interview plans with competency-based questions and scorecards. Trigger with "interview plan for", "interview questions for", "how should we interview", "scorecard for", or when the user is preparing to interview candidates.

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。

Track and manage recruiting pipeline stages. Trigger with "recruiting update", "candidate pipeline", "how many candidates", "hiring status", or when the user discusses sourcing, screening, interviewing, or extending offers.

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。

Analyze indexed codebases via graph database (neug) and vector index (zvec). Covers call graphs, dependencies, dead code, hotspots, module coupling, architecture reports, semantic search, impact analysis, bug root cause from GitHub issues, class diagrams (UML), and PR review (risk scoring, conflict detection, auto-merge candidates, labeling). Also covers creating, inspecting, and repairing a CodeScope index. Use for: code structure, who calls what, why something changed, similar functions, module boundaries, bug tracing, class relationships, PR risk/conflicts, or any question benefiting from a code knowledge graph. Applies when a `.codegraph` index exists in the workspace, or when the user wants to create one.

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。

Use for a periodic repo-wide sweep of qwen-code for accumulated excess surface — dead components and files, orphaned locale keys, exports nothing consumes, added-then-removed scaffolding — filing candidates on a tracking issue and landing only what a maintainer has said yes to. Repo-wide and evidence-first; every consumer is named before anything is deleted. Not for tidying a diff you just wrote (that is bundled `/simplify`) and not for defects (that is `/review`).

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。

Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:memory-review or asks what has been learned and what should be promoted or pruned.

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。

Build and maintain one coherent company story across all audiences — employees, investors, customers, candidates, and partners. Detects narrative contradictions and ensures the same truth is framed for each audience's needs. Use when preparing investor updates, all-hands presentations, board communications, recruiting narratives, crisis communications, or when user mentions company narrative, messaging consistency, storytelling, all-hands, investor update, or crisis communication.

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。

Find high-priority open NemoClaw security PRs to review, including competing or superseded candidates.

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。

Prepare the NemoClaw morning maintainer plan: triage the backlog, select a target version, and identify release candidates and stragglers.

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。

Review Apache ShardingSphere or user-authorized downstream pull requests and PR discussions from public or authorized repository evidence. Use for code-correctness or mergeability decisions, CI-focused review, root-cause and regression analysis, complete consolidated findings, copy-ready committer feedback, challenged findings, multi-round review, and formal review of local implementation candidates in the repository completion loop.

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。

Daily interview-scheduling sweep for {{projectName}}. Reads {{greenhouse_pipeline}} for candidates ready to schedule and each one's interview plan, checks {{interviewer_calendars}} for panel availability, and drafts a candidate slot proposal plus a calendar invite per interviewer to {{coordinator_review_inbox}}. Never sends a proposal or invite and never makes a hiring decision; a coordinator confirms and sends everything.

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。

Daily outbound-sourcing sweep for {{greenhouse_role}}. Searches LinkedIn for candidates matching {{sourcing_criteria}}, dedupes every match against the role's Greenhouse pipeline, and drafts a personalized outreach email per new candidate to {{recruiter_review_inbox}} — capped at {{daily_cap}} per run. Never sends outreach and never writes to Greenhouse; the recruiter reviews, sends, and owns the ATS.

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。

Divergent ideation and corpus expansion via Verbalized Sampling plus extended thinking — single-shot generates several internally diverse candidates and surfaces the strongest, or expands a seed corpus into a diverse dataset for evals and test sets. USE WHEN be creative, brainstorm, divergent ideas, creative solutions, maximum creativity, tree of thoughts, radically different, name this, creative angle, expand this corpus, synthetic data, generate diverse examples, create test set. NOT FOR multi-cycle evolutionary ideation with Lamarckian meta-learning (use Ideate).

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。

Evolutionary ideation engine — loop-controlled multi-cycle idea generation through phases of dreaming, cross-domain stealing, recombination, fitness testing, selection, and Lamarckian meta-learning, producing ranked novel solution candidates with provenance. USE WHEN ideate, id8, novel ideas, evolve ideas, dream up solutions, innovate, breakthrough ideas, idea evolution, multi-cycle creativity, need genuinely new approaches. NOT FOR quick single-pass brainstorming (use BeCreative).

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。

Analyze a site's backlink profile, anchors, toxic signals, competitors, gaps, and disavow candidates. Use only when links or referring domains are the requested focus.

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。

Automate recruiting and hiring workflows in Ashby -- manage candidates, jobs, applications, interviews, and notes through natural language commands.

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。

Use git heatmap analysis to identify high-churn files and lines as candidates for thorough review or bug hunting. Works for PR reviews, security audits, bug hunts, or any code analysis task.

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。

Expands one confirmed or suspected vulnerability into a Trailmark graph neighborhood of variant candidates by finding sibling functions, shared callers and callees, common sensitive sinks, common entrypoint paths, interface implementations, override relationships, type/reference neighbors, and structurally similar nodes. Use after one issue is found to seed variant-analysis, semgrep-rule-creator, static-analysis, or manual review with graph-derived candidate locations.

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。