调研、论文、教育、考证学习（4472 个）
Analyse the language demands of a classroom task to identify barriers for EAL and multilingual learners. Use when adapting tasks, planning support, or assessing linguistic accessibility.
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Build a learning progression showing prerequisite-to-mastery steps for a target skill or understanding. Use when sequencing content, designing diagnostics, or mapping prerequisite gaps.
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Author learning targets for a competency across developmental bands with precise, observable progression language. Use when writing 'I can' statements for competency-based programmes.
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Analyse existing written feedback for quality, specificity, actionability, and impact on student learning. Use when reviewing teacher or peer feedback to improve feedback practices.
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Adapt a classroom task for specific learner needs while preserving the core learning objective intact. Use when differentiating for SEND, EAL, gifted, ADHD, dyslexia, or anxiety.
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Select the right formative assessment technique for a specific learning moment, purpose, and age group. Use when choosing how to check understanding during, between, or after lessons.
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Track performance across sessions and reduce scaffolding as competence grows. Makes fading visible — the learner knows when scaffolds are removed and why. Use for sustained learning engagement where independence is the goal.
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Authors or reviews Know/Understand/Do charts for competency-based learning targets across developmental bands. Handles seven input types from raw curriculum documents to existing LT sets. Routes to upstream skills when stronger inputs are available.
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Analyse student work against criteria to identify specific gaps between current performance and learning objectives. Use when reviewing submissions, planning feedback, or diagnosing learning needs.
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Create an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.
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Map which elements of an assignment benefit from AI assistance vs. which AI use undermines. Use when redesigning tasks for AI-age classrooms or setting defensible AI use policies for specific assignments.
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Unpack a broad standard or competency descriptor into specific, assessable success criteria and sub-skills. Use when interpreting curriculum standards or writing learning objectives.
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Build a five-level rubric with coherent logic for a learning target within a developmental band. Use for Manning methodology programmes where Competent = success. For general curriculum rubrics, use criterion-referenced-rubric-generator instead.
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After any AI-generated explanation, require the learner to identify one place it could be wrong, one thing to check, and one source to consult. Builds epistemic vigilance — treats AI output as a claim to evaluate, not truth to absorb.
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Generate tiered sentence frames for academic tasks that scaffold language production across proficiency levels. Use when EAL students need structured language support for classroom discourse.
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Generate scaffolds that gradually increase student choice, voice, and ownership within a learning task. Use when students depend heavily on teacher direction and need to develop autonomy.
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Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.
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Document a recently solved problem or durable project vocabulary in docs/solutions/ or CONCEPTS.md. Use when capturing a learning after work.
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When the user wants to find, qualify, and build a list of prospects to reach out to — across B2B SaaS, general B2B, or local small businesses. Also use when the user mentions "prospecting," "build a prospect list," "find prospects," "find leads," "lead gen list," "find SaaS companies that," "find B2B companies," "find local businesses," "ICP-fit accounts," "who should we go after," "outbound list," "target account list," "find clients near me," "businesses without websites," "prospect research," or "qualified leads." Use this for the list-building and qualification phase. For writing the outbound copy after the list is built, see cold-email. For deep competitive research on specific accounts, see competitor-profiling.
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When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.
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技術的な不確実性が大きい実装（方式が使えるか、仕様やライブラリが実際にどう振る舞うか、性能や精度が足りるかが動かさないと分からない）を、調査→使い捨てMVP→精査と実験→仕様→MVPの破棄→再実装→報告の順に進める。作業の重さがレベルRのときに使う。'MVPを作ってから作り直して'、'一度試作して捨てて'でも使う。要件が曖昧なだけの作業、既知のパターンで書ける作業、調査だけの依頼には使わない。
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既存のコードやシステムが今どう動いているか（仕組み、処理の流れ、どこに何があるか、どの層やモジュールが持つべきか）を、コードを読んで説明する。'どうなっているか'、'仕組みを教えて'、'この処理の流れ'、'これはどこに置くべきか'、変更の前に既存の仕組みを理解したいときに使う。なぜ今の形なのか（経緯）は`why`、技術の選定は`research`を使う。
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作業の種類（不具合の修正、機能の追加・変更、リファクタリング、性能の改善、調査）ごとの手順書。作業の重さを決めた直後に、当てはまる手順書を読んで、その順に進める。'このバグを直して'、'不具合'、'機能を追加して'、'リファクタリングしたい'、'遅い'、'速くして'、'/playbook'で使う。
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既存のコードや設計がなぜ今の形なのか、なぜその選択をしたのか、退行や障害の経緯、しきい値の根拠を、git・GitHub・Notion・Slackなどの記録から調べ、確からしさを区別して出典付きで答える。'なぜこうなっているのか'、'この値はどこから来たのか'、'この設計にした理由'、コードを変える前に経緯を確かめたいときに使う。コードが今どう動くかの説明（howを使う）や、新しい技術の選定（researchを使う）には使わない。
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