「complete」の検索結果

Audit your Obsidian vault in Claude Code — finds stale drafts, empty folders, duplicate filenames, and incomplete files. Saves a dated report.

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。

Run complete TDD red-green-refactor cycle for a test

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This skill should be used as a mandatory final sanity check before git commit, PR creation, or declaring work done. Triggers on "commit", "push", "PR", "pull request", "done", "finished", "complete", "ship", "deploy", "ready to merge". Catches security vulnerabilities, logic errors, and business rule bugs that slip through despite passing tests.

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Trigger for: finding federal opportunities; capture and bid screening; competitor or incumbent intelligence; recompete pipelines; teaming partner research; agency, customer, or market intelligence; federal labor-rate or pricing context; or refreshing prior GovCon research. Always begin with the complete workflow menu and obtain the user's selection before research, preflight, file generation, web search, or MCP calls. Produce sourced chat findings or an optional validated GovCon Growth Brief without making a bid decision from public data alone.

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Translate a complete mathematical modeling contest problem sentence by sentence into precise modeling language, preserve every substantive condition and definition, expose hidden constraints, draw a mandatory Mermaid cross-question flowchart, audit omissions, and deliver one easy-to-open Markdown report. For Huawei Cup (CPGMCM) graduate-contest problems, additionally prepend a plain-language layer that rewrites the background and questions as a primary-school word problem with a mandatory term-mapping table. Optionally render the finished report as one standalone HTML page on request. Use whenever a user supplies a CUMCM, CPGMCM, or other modeling problem and asks to interpret, translate, unpack, read closely, identify requirements, or avoid missing details before modeling.

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Generate a coherent, whole-paper mathematical modeling solution framework from a complete contest problem. Use after the user supplies a CUMCM or other modeling problem and asks for modeling ideas, an overall solution plan, question-by-question analysis, candidate-model comparison, model-selection reasons, innovations, validation, or cross-question linkage. For every question, explain the task and mathematical essence, compare multiple feasible models in tables, recommend a route with explicit reasons, and keep all questions connected through shared data, variables, parameters, constraints, and validation.

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Review the model establishment, numerical solution, result analysis, model validation, and sensitivity or robustness sections of a mathematical-modeling paper against the complete problem. Use for core-model-section diagnosis, not automatic full-paper scoring or unsupported recomputation.

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Generate or review mathematical-modeling competition AI tool usage statements and the anonymous AI工具使用详情.pdf. Use when users provide real AI usage records, or when checking a paper, statement, details PDF, code, and AI records for completeness, anonymity, and consistency.

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Generate a compliant Chinese mathematical-modeling problem-restatement chapter from a complete problem statement, or review a user's restatement against the original problem. Covers research background, problem review, and research overview; does not perform the separate problem-analysis chapter.

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Review a mathematical-modeling paper's model-assumption section against the complete problem statement. Diagnose whether each assumption is necessary, evidence-based, compatible with the task, appropriately simplified, and usable by the later model. Use for assumption review, not automatic full-paper review or unsupported assumption generation.

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Review mathematical modeling competition papers from a complete problem and paper, with an optional strict bzd-paper-format-checker audit, itemized problem-specific scoring, a bottom-up low-score safeguard, and CUMCM award calibration by problem type, division, region, school and advisor. Generate a Chinese HTML judge report.

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Review a complete mathematical-modeling competition paper with an atomic checklist covering abstract readability, page structure, typography, headings, pagination, figures, tables, equations, anonymity, metadata, visual balance, and page allocation. Return the review in chat or Markdown by default, and provide the bundled single-sheet checklist when the user requests a reusable form. Use when the user provides a PDF or Word paper and asks for a full-paper format and writing-compliance audit; do not replace technical model correctness review.

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Enhancement-overlay SOP for adding sparse (BM25 / keyword) retrieval alongside dense (embedding) retrieval. Activate when a calling agent is building, reviewing, or debugging a retrieval pipeline whose corpus contains exact-match tokens — identifiers, error codes, SKUs, API/function names, proper nouns, citations, rare jargon — that pure dense embedding silently misses. Encodes the single decision rule (**hybrid is traffic-driven, not theoretical: add sparse only when the query share that depends on exact tokens is non-trivial**), the wiring of QueryFusionRetriever-style fusion (RRF vs alpha-weighted), and per-query-type alpha tuning. Frame the work as recovering lexical identity that dense pooling destroys, not as "add keyword search for completeness". Cross-links [[llamaindex]].

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Presents options for merge, PR, or cleanup. Use when work is complete, tests pass, and you must decide how to integrate.

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Automatic review gate that runs after brainstorming completes - spawns PM, Architect, Designer, Security, and CTO agents in parallel, iterates until all approve

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This skill should be used when the user asks to "做一个剪纸广告", "制作拼贴广告片", "把产品做成纸片定格动画", "做一个有趣的产品广告", "生成半色调剪纸分镜", "把静态拼贴图做成广告视频", "把广告拉长一点", "参考这个声音配音", or wants a complete branded paper-cut advertisement from brief to validated MP4 rather than only prompts or still images.

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Consult ChatGPT Pro via ChatGPT browser automation for problems that resist standard approaches. Use when stuck on a very hard problem, when standard approaches have failed, when multiple debugging attempts haven't worked, or when the user says "ask the oracle", "consult oracle", "consult chatgpt", "I'm completely stuck", "I've tried everything", or "nothing is working".

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Validates entire engineering proof chain. Verifies architecture, backend maps, backend code, standardization, frontend types, infrastructure topology all compose correctly. This is the final DEPLOYMENT GATE - deployment blocked if proof chain invalid. Use when engineering thread completes all actions.

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Complete browser automation with Playwright. Auto-detects dev servers, writes clean test scripts to /tmp. Test pages, fill forms, take screenshots, check responsive design, validate UX, test login flows, check links, automate any browser task. Use when user wants to test websites, automate browser interactions, validate web functionality, or perform any browser-based testing.

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This skill should be used when drafting GitHub issues for the Positron repository. It provides workflows for searching duplicates, selecting appropriate labels, gathering complete context through questioning, and writing terse, fluff-free issues that precisely describe what is needed or wrong. The skill prepares issues for manual submission by the user. Use this skill when the user asks to draft or prepare an issue for Positron.

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Jewish and Hebrew wisdom - Order before creation, Kabbalah Tree of Life, Gematria navigation, Talmudic argument as collision, Tzimtzum incompleteness

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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

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。

Validate consistency across SEED Design component documentation layers (design guidelines in ./docs/content/docs/components, Rootage specs in ./packages/rootage/components, and React docs in ./docs/content/react/components). Use when auditing documentation completeness, before releases, or validating new component docs.

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Complete Product Owner / Product Manager capability — a wiki-style knowledge map of product practice in active software development: the role and its boundaries, strategy cascade (vision → OKRs → roadmap → backlog), continuous discovery, backlog craft (epics, INVEST stories, acceptance criteria), prioritization frameworks (RICE, MoSCoW, Kano, WSJF), sprint delivery, metrics (North Star, AARRR), stakeholder management, and anti-patterns. The PO/PM owns what gets built, in what order, and why — including the end-to-end user flows and user journeys. Use when scoping a product or feature, decomposing an idea into outcomes/epics/stories, prioritizing a backlog, defining an MVP, mapping user journeys, measuring success, or saying no to a stakeholder. Pairs with super-ui-ux-design, which owns how each screen looks and behaves.

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。