「score」の検索結果

IT要求・活動インパクトスコアの検証を行う時の観点を説明する

Create a look-alike audience from a seed audience and a candidate population dataset. Classifies Rosetta Stone attributes, generates the same materialized-view scoring pipeline Lookalike Studio emits (Naive-Bayes categorical weights + Gaussian continuous similarity), gates on approval, submits via `narrative_workflows_create`, and monitors the build to completion. Use when: "create a lookalike audience", "find more users like this segment", "expand my seed audience to 500k similar users", "score the population against my customers", "build a look-alike of dataset X". (narrative-audience)

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。

Compare standardized metrics across multiple ego-benchmark-harness runs by recalculating them from tasks.jsonl and session JSONL, never from HTML reports. Covers overall aggregates (success rate/average score), Odysseys per-rubric pass rates, duration distributions (avg/p50/p90/max), turns/tools/cost, error and exception counts, per-task success matrices, helper distributions, and the share of DOM operations. Use whenever users ask to compare data or metrics across runs, calculate aggregate/Odysseys/duration/turn/error/helper metrics, inspect differences among runs, or compare multiple rwb/real-world-bench runs. Use pi-session-analyzer instead for deep forensic analysis of why an individual task was slow or failed.

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。

Econometrics skill for instrumental variables and treatment effect estimation. Activates when the user asks about: "instrumental variables", "IV estimation", "2SLS", "two-stage least squares", "endogeneity", "weak instruments", "first stage", "Sargan test", "overidentification", "propensity score matching", "PSM", "average treatment effect", "ATT", "LATE", "local average treatment effect", "endogenous regressor", "instrument validity", "工具变量", "两阶段最小二乘", "内生性", "弱工具变量", "倾向得分匹配", "平均处理效应", "处理效应", "局部平均处理效应"

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Многомодельная оркестрация и стратегия переключения моделей. Выбор моделей на основе оценки (score), делегирование между агентами (Gemini, Codex, Ollama), связывание с advisor, триггеры эскалации, матрица разрешений и оптимизация затрат.

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。

Komponiert video-synchronisierte Hintergrundmusik aus einem Storyline-JSON per lokaler Waveform-Synthese (numpy + ffmpeg). Stile: Chiptune, Ambient, Electronic. Deterministisch, offline, kein Cloud-Dienst.

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。

Reviews one deal's notes and timeline (CRM opportunity record, activity log, emails, meeting notes, forecast entries) for risk signals such as a single contact thread, no identified budget owner, slipped or missing dates, silence after a proposal, an undefined decision process or a competitor named late, and returns a DRAFT risk register: each signal with the quoted evidence and its date, a severity on a stated scale, and one proposed next action with an owner role for the user to decide on. Use when the user asks to "review the risks on this deal", "why is this opportunity stalling", "is this deal single-threaded", "deal health check before the forecast call" or "what should we do next on <opportunity>". Do not use for a whole-account plan, use account-plan-builder instead; for scoring early leads against a rubric use lead-qualification-scorer. Drafts for human review; never approves, authorises or signs off.

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。

Prepares a discovery call brief from what the user has on a prospect (CRM record, inbound form, emails, notes, public material the user supplies): what is known with sources, gaps against the qualification dimensions, hypotheses to test, questions in priority order and what to listen for. Returns a DRAFT Markdown brief in the chat. Use when the user asks to "prep me for the discovery call with <prospect>", "what should I ask on this first call", "intro call brief", "questions for the qualification call" or "what do we know before we speak to them". Do not use for scoring leads against a rubric, use lead-qualification-scorer instead; for an existing customer's account review use account-plan-builder. Drafts for human review; never approves, authorises or signs off.

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。

Prepares a DRAFT vendor risk screening brief from the material the user provides on one vendor (questionnaire answers, certificates, assurance reports, policies, contract extracts): per screening topic, what a document evidences with reference, date and scope, what is only asserted, what is missing or contradicted, certificate and report details as stated, and ready-to-send questions for the vendor and the internal owners. No web research, no risk rating, tier, score or recommendation. Use when the user asks to "screen this vendor", "review the vendor's questionnaire answers", "check what the vendor's certificate covers", "what is missing from this due diligence pack" or "draft the follow-up questions for the vendor". Do not use for answering a customer's questionnaire about your own organisation, use vendor-security-questionnaire-prefill instead. Drafts for human review; never approves, authorises or signs off.

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。

Reads a risk register together with meeting notes and incident reports and returns a draft update pack: existing risks whose exposure, controls, ownership or status the sources say have changed, new risk candidates, closure candidates, and the one owner decision each item needs. Never assigns or changes a likelihood, impact, score or colour and never edits the register; owners decide. Use when the user asks to "update the risk register from these minutes", "refresh the register with the incidents since the last review", "reconcile the register against the notes" or "what changed on our risks". Do not use for writing up an incident itself, use incident-postmortem-drafter or data-incident-impact-brief instead; to track actions from minutes, use corrective-action-tracker. Drafts for human review; never approves, authorises or signs off.

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。

Reads two or more supplier, bid or tender responses against a requirements list and returns a DRAFT comparison pack: a requirement-by-supplier matrix, gaps per supplier, clarification questions and neutral observations, for an evaluation panel. Never scores, weights, ranks or recommends a winner; the award stays with the panel. Use when the user asks to "compare these bids", "matrix the tender responses against our requirements", "collate the RFQ replies", "show me where each supplier falls short" or "draft clarification questions for the bidders". Do not use for scoring or weighting against agreed criteria, use supplier-evaluation-matrix instead, or for writing the requirements, use rfp-requirements-pack instead. Drafts for human review; never approves, authorises or signs off.

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。

Drafts a DRAFT self-assessment, peer feedback note or manager review narrative from the evidence the writer supplies (goals, examples, metrics, notes), in the review template where given: every sentence tied to a numbered evidence item, unsupported claims removed and logged, and a gaps list to complete before submitting. Never assigns, suggests or implies a rating, score, ranking, pay or promotion outcome. Use when the user asks to "write my self-assessment", "draft peer feedback for a colleague", "turn these notes into a performance review", "help me write the year-end review for my report", "summarise my achievements against my goals" or "draft the mid-year review". Do not use for a job description or role profile, use job-description-drafter instead; for a new hire's first 90 days, use onboarding-plan-builder. Drafts for human review; never approves, authorises or signs off.

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。

Turns a business need and its constraints into a DRAFT RFP requirements pack: traced functional and non-functional requirements with priorities, mandatory gates, evaluation criteria with weights left to the business owner, and fact-seeking supplier questions. Solution-neutral; never names a supplier or product. Use when the user asks to "write the RFP requirements", "turn this business case into tender requirements", "draft the supplier questionnaire", "structure our RFQ from this brief" or "set up evaluation criteria before we go to market". Do not use for responses already received, use rfp-comparison-pack to compare them or supplier-evaluation-matrix to score them instead. Drafts for human review; never approves, authorises or signs off.

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。

Reviews one SKILL.md against the format rules and returns a findings table: strict YAML front matter with exactly name and description, name equal to the folder, description as the trigger, the eight-heading skeleton, capability-neutral wording, safety boundaries. Each finding carries severity, rule identifier, location, quoted evidence and replacement text; the verdict READY, REVISE or BLOCKED is an apparent state and the owner decides. Use when the user asks to "review this SKILL.md", "check my skill file before upload", "lint this skill description", "validate the front matter of this skill" or "score this skill folder". Do not use to write an agent's instructions field, use agent-instructions-drafter instead; for injection or leakage exposures use agent-instructions-red-team; for launch tests use agent-evaluation-plan. Drafts for human review; never approves, authorises or signs off.

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。

Synthesises a batch of customer feedback (survey answers, reviews, ticket and chat comments) into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim quotes cited to record codes, contradictions and unverified claims, and the follow-up questions to answer next. Produces no sentiment score or percentage positive as fact; ratings appear only as distributions with n. Use when the user asks to "theme this feedback", "what are customers saying", "summarise these survey answers", "analyse these reviews", "find the top complaints in these comments" or "code this voice of the customer data". Do not use for exit interviews, use exit-interview-synthesis instead; for sorting a live queue and drafting replies, use ticket-triage-pack; for project retrospectives, use lessons-learned-synthesis. Drafts for human review; never approves, authorises or signs off.

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 focus and context switching over a chosen period without inventing productivity scores.

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。

Audits a live website for AI-engine discoverability (AEO/GEO). Crawls the site, runs 16 deterministic checks plus a 6-dimension content evaluation, and produces a scored report (A-F) with prioritized fixes. Use to get a baseline before improve-aeo-geo, or to measure progress after changes.

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。

Design and interpret TypeSafe Jev decision requests in NV oOS — typed choice/score/noul questions, batching, confidence thresholds, composite scoring, and guardrails. Use when classifying, routing, scoring, or safety-screening content with the typesafe_decide or typesafe_guardrail tools.

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。

The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA aud

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。

Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.

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。

Scores shortlisted accounting packages against 57 evidence-backed fields, emitted as CSV, SQL, JSON Schema or Notion on request. Use for choosing accounting software.

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。

360 feedback register: reviewer, subject, review cycle, visibility, due date and score, as CSV, SQL, JSON Schema or Notion on request. Use for 360 reviews or peer feedback cycles.

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Use when the user asks to "run the weekly social readout", "which denominator does our engagement rate use", or "which posts won this week and what changes next cycle"; produces the organic-social metric dictionary (every rate names its denominator — ERR engagement-by-reach vs ERI by-impressions vs ER-by-follower — locked across periods), median-not-mean per-post rollups with organic and boosted separated, EMV as labeled exec-translation only (never inside any score), an attributed CHAOSS/Orbit-style community-health readout with employees excluded, and the best/worst-performer write-back the next calendar cycle consumes. Not for dollar-ROI math or the ECHO profile result gate verdict — use roi-calculator and social-quality-auditor. 社媒周报/互动率分母/指标字典/复盘回写

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Use when the user asks to "find trending topics", "what trends should my brand jump on", or "time a campaign around a cultural moment"; produces a ranked trend report with brand-fit scores, format calls (rising/peak/declining), a cultural calendar, and go/skip recommendations. Not for finding the creators to run those trends — use influencer-discovery; not for building the brand posting calendar from a go verdict — use social-calendar-builder. 热点趋势洞察/借势营销

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。