「rubric」の検索結果

Use when scoring finished content against quality dimensions, evaluating whether a piece meets publishable standards, or determining which workflow phase needs rework based on quality gaps.

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Create evaluation frameworks for AI outputs with rubrics and scoring. TRIGGERS - Use when user needs help with ai-evaluation-framework related tasks.

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Use when evidence needs grading before anyone reasons from it — the user asks "how reliable is this?", "grade this source", "check this report", "can I trust this article?", "is this corroborated?", or hands over a URL, a pasted report or a Liberty91 event ahead of an ACH or assessment. The Quality of Information Check from the CIA Tradecraft Primer, adapted for vendor and press CTI reporting. Resolves each document to its originating source, splits it into claims, and grades every claim on two written elements, access level (how the source knows) and claim support (what backs the statement), with a stated rationale, using a fixed rubric with hard caps. The grade is not an Admiralty rating. Five outlets citing one vendor report count as one source; anything that cannot be traced to a primary is capped, not guessed. Returns a graded claim table, gaps, a deception screen and JSON. /ach, /threat-assessment and /writing-assessments run it first by default.

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Validates agent definitions against the Antigravity audit rubric.

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Build structured behavioral interview guides using the STAR method. Map job competencies to interview questions, provide scoring rubrics (1–5), and include follow-up probes and red/green flag indicators. Use when preparing for hiring interviews or standardizing interview practices.

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Use when a task needs the judgment of an English Language and Literature Professor — backward-designing a first-year composition or literature syllabus against a shared outcomes rubric, deciding whether an AI-detection or plagiarism flag on a student essay warrants an integrity case, reading where a tenure case's monograph actually sits in a university press's pipeline, or handling a content complaint about an assigned literary text.

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Use when a task needs the judgment of a Communications Teacher, Postsecondary — designing or norming a multi-section basic public-speaking course, resolving a cross-rater grading discrepancy on a speech rubric, screening for and accommodating communication apprehension, or choosing a rhetorical-criticism method for a media-analysis assignment.

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Standalone E-E-A-T scoring rubric for a URL or content draft. Scores Experience, Expertise, Authoritativeness, and Trust 0-5 each using concrete detectable signals, framed per Google's creating-helpful-content doc. Use when user says "E-E-A-T", "EEAT", "experience expertise", "trust signals", or "author authority".

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Generate a complete structured interview kit for a role — 3-5 role-specific competencies, one behavioral (STAR-format) question per competency, 1-5 scoring rubric with explicit behavioral anchors at each level, per-panel scorecards, interviewer debrief template.

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Improve an existing agent SKILL.md through one gated cycle: select the target (default this skill), snapshot the committed baseline, diagnose against skill-design-principles plus four rubric dimensions, apply exactly one focused change, and ship only if a different agent than the author PASSes with quoted evidence. Use when the user says "improve this skill", "improve-skill", "iterate on SKILL.md", or "apply skill-design-principles to a skill". Do not use for code slop over a duration (anneal), generic timeboxed work (timeboxed-iterating), graph orchestration (workgraph), metric hill-climb on a codebase (autoresearch), or stripping slop from existing prose (catalog-deslop).

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สร้างแผนการสอน + แบบฝึกหัด/quiz + rubric การประเมิน + ไอเดียการบ้าน สำหรับครูไทยทุกระดับชั้น

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Auto-assembles a domain-specific expert panel (7–10 experts), scores any content or strategy artifact against a typed rubric, and iterates until the aggregate hits 90+ (max 3 rounds). Use as a quality gate on copy, email sequences, landing-page drafts, strategy docs, charts, titles, or recruiting evaluations — or when another skill needs a final review gate on its output. Triggers on "expert panel this", "score this", "rate these variants", "quality check this", "panel review", "expert score", "evaluate this copy/strategy/page". For variant generation and multi-round conversion optimization see autoresearch; for live-URL CRO auditing see conversion-ops; for the scripted content-production pipeline see content-pipeline.

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Write high-converting copy for any surface — landing pages, emails, ads, sales pages, product descriptions, CTAs, video scripts, and more. Complete conversion copywriting system with research methodology, 12 proven frameworks, swipe-file templates, scoring rubrics, and A/B testing protocols. Use when you need to write or review any copy meant to drive action.

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Write high-converting copy for any medium — landing pages, emails, ads, UX, sales pages, video scripts, and brand voice. Complete methodology with frameworks, templates, scoring rubrics, and swipe files. Use when writing or reviewing any user-facing text.

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Code auditor that grades software projects and the agents/developers who built them. Produces structured JSON + Markdown reports with a standardized rubric. Evaluates architecture, correctness, testing, authorship cohesiveness, ghost code, and more. Optionally ingests tmux session logs for process evidence and interrogates agents about specific problems found. Use when asked to "audit", "grade", "evaluate", "review code quality", "rate this project", "score the agents", or "assess the codebase". Especially useful after Marcus multi-agent experiments to grade agent output and track quality over time.

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Autonomous goal loop — give it ONE goal plus how to verify it, the agent runs check→fix→check itself and comes back only with the finished result (code with audit, research with fact-check, content with critique, audit/backtest). Self-verification instead of constant supervision, with hard safety guards. Vary the loop with a verification rubric designed before it runs. Triggers — "work autonomously to the result", "don't come back until it's done", "run the loop yourself", "drive it to done".

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Content-addressed baseline-archive epoch partitioning. Partition baseline_archive.jsonl + the self-improving hub's baseline serving by a HASH of the full baseline-production+measurement spec — when the spec (margin_rule, fitness/margin logic version, the 4 roles' model+source, rubric/dim-set, bench, seed-pool identity) changes, the hash changes → a new epoch series (like seed-gen gen-*). Triggered by "baseline epoch", "baseline 아카이빙", "epoch partition", "spec hash", "content-addressed", "margin_rule namespace", "production logic 구분", "baseline 하위 서빙" keywords.

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Negotiates a file-based sprint contract between generator and evaluator before code is written: turns a spec into testable acceptance criteria with rubric tie-ins.

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Experimental behavioral evaluator. Drives a running artifact via browser/curl/CLI and records rubric evidence; the runner is not yet a fully implemented automated evaluation system.

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Parameterized evaluator-optimizer loop for quality-critical output with configurable rubrics

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Quantitative agent evaluation using 4-metric framework (correctness/step_ratio/tool_call_ratio/latency_ratio) with ideal trajectory annotation and capability-categorical taxonomy. Use when measuring agent efficiency, comparing agent variants, or gating new agents through correctness→efficiency phases. Complements harness-eval (SE benchmarks) and evaluator-optimizer (qualitative rubric).

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Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, or distinguishing the automatable evidence from the case-specific evidence requiring manual input.

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This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

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T+N 天数据回收 + 复盘 + 把实绩观察写入 rubric-memo.md。这是校准循环的反馈环节——不复盘的预测等于占星。触发词："复盘 [path]"/"retro this"/"T+3d 数据来了"/"抓数据 [path]"/"把这篇复盘了"。

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。