리서치·학습 스킬

Use before any research activity or significant decision. Reviews cognitive biases relevant to the current stage.

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Evaluates ML applications in investment with feature engineering, model selection, and implementation considerations for alpha generation. Use when evaluating ML for investing, designing ML pipelines, or assessing ML strategy feasibility.

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Measures implementation shortfall with paper portfolio comparison, delay cost attribution, and execution quality assessment. Use when measuring implementation shortfall, analyzing execution quality, or attributing trading costs.

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Evaluates amendment and waiver requests with consent requirements, fee structures, and modified term impact analysis. Use when analyzing amendments, structuring consent solicitations, or evaluating covenant relief requests.

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Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team

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Simulate rigorous, fair peer review on a paper — in two modes. (A) Red-team YOUR OWN draft before submission to predict the reviews you'll get and get a fix list. (B) Review SOMEONE ELSE'S paper when you're an assigned reviewer or helping your advisor — produce a fair, venue-formatted, submission-ready review. Use whenever the user gives a paper (PDF, .tex, .md, arXiv link, or pasted text) and wants to predict reviews, find weaknesses before reviewers do, stress-test a submission, OR write a real review of another paper. Grounded in official NeurIPS/ICLR/ACL reviewer guidelines; every criticism pinned to a location, and checked against ACL's H1–H17 list of illegitimate critiques. 两种模式:审自己的稿(投稿前红队)/ 审别人的稿(当审稿人或帮导师),按会议官方标准评,绝不脑补、绝不发不正当批评。

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Captures project-specific patterns and anti-patterns into the project's configuration file. Loaded by other skills (bug-killer, feature-dev, etc.) when they discover project-specific knowledge worth encoding for future sessions.

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Captures project-specific patterns and anti-patterns into the project documentation. Loaded by other skills when they discover project-specific knowledge worth encoding for future sessions.

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Solve competitive programming and LeetCode-style problems with educational explanations. Use when asked to "solve this problem", "help with this leetcode", "competitive programming solution", "solve this algorithm problem", "coding challenge solution", "how to solve this coding problem", or any algorithmic problem-solving request.

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Create a new specification through an adaptive interview process with proactive recommendations and optional research. Use when user says "create spec", "new spec", "generate spec", or wants to start a specification document.

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Captures project-specific patterns and anti-patterns into the project's CLAUDE.md. Loaded by other skills (bug-killer, feature-dev, etc.) when they discover project-specific knowledge worth encoding for future sessions.

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Conduct an adaptive interactive interview on any topic and produce a structured markdown report, summary, or implementation plan. Use when the user says "interview me", "interview me about", "run an interview on", "help me think through", or wants guided discovery on any subject. Also triggers on "talk me through", "explore X with me", "help me plan Y", or "walk me through my thinking on Z" when the user wants a guided conversation rather than a direct answer. Applies broadly — career decisions, project ideas, product direction, personal goals, research questions, team problems — not just technical topics.

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Research-backed template refresh workflow for updating existing templates with placeholder verification and rendering validation.

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Research-backed skill refresh workflow for updating existing skills with TDD checkpoints, memory-aware integration, and EVOLVE/reflection trigger handling.

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Search and read public Reddit posts, subreddits, and comments via the unauthenticated JSON API. Safe read-only access with SSRF-prevention hostname allowlist.

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Manus-style file-based planning for complex tasks. Use task_plan.md, findings.md, and progress.md to maintain persistent context. Use for multi-step tasks, research, or work spanning many tool calls.

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Research best practices and synthesize into design decisions for artifact creation. Invoke BEFORE any creator skill to ensure research-backed decisions.

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Research-backed JSON Schema refresh workflow for updating existing schemas with validation checkpoints and cross-reference verification.

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Records atomic learned behaviors with confidence scores. Project-scoped instincts are isolated per project and auto-promote to global scope at confidence threshold 0.8. Stores instincts in .claude/context/memory/instincts.jsonl

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Extract actionable insights from completed coding sessions. Use when a session completes to capture learnings for future sessions.

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Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines.

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Research-backed hook refresh workflow for updating existing hooks with TDD checkpoints and settings.json registration validation.

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Multi-step autonomous research methodology for deep investigation tasks with structured synthesis

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Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.

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