“csv”的搜索结果

Local-only regression / benchmark skill for ui-clone-skills maintainers. Drives the standard ui-reverse-engineering pipeline against the canonical reference site (https://realfood.gov) and records AE/SSIM, iteration count, gate fail counts, and outcome to benchmark/history.csv so prompt / sub-doc / model-version drift surfaces as a trend. Trigger phrases: "run benchmark" / "regression benchmark" / "benchmark clone". The Makefile no longer has a `benchmark` target — setup is inline bash in this skill (Step 1 below). Internal: NOT registered in `.claude-plugin/plugin.json` `skills`. Not part of the public 3-skill marketplace surface. Maintainer tooling only.

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Annotate speech/TTS datasets with per-clip quality metrics (MOS, SNR, STOI, pitch, bandwidth, speaking rate, WER/CER, gender/emotion), multi-ASR consensus transcription and speaker labeling using the audiogear pipeline; then filter clips by quality and build listenable HTML QA reports. Use when asked to compute audio dataset metrics, build extended_metadata.csv, transcribe unlabeled audio, select clean TTS training data, or QA a speech dataset.

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学术论文图表生成与设计。输入是实验数据（CSV/表格）、图表草稿、论文方法描述、中文图/表说明、想生成的图形摘要（GA）、或想画流程图时使用。功能包括：matplotlib 绘图（plot）、图表类型推荐（recommend）、英文图/表标题生成（caption）、论文架构图 prompt 生成（architecture）、图形摘要 prompt 生成（abstract）、流程图 prompt 生成（flowchart）、图表规范检查（polish）、概念图/示意图设计（design）。架构图模板覆盖 6 类场景，流程图覆盖 6 类（线性 / 分支 / 并行 / 循环 / 嵌套 / 泳道），图形摘要覆盖 5 类。内置 prompt 工程词汇表与参数化语法。不适用于：正文段落润色（用 academic-writing）、参考文献格式（用 academic-citation）。

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Shared corpus-grounding engine — BM25 + structured filters + decision rules over CSV corpora via a domain manifest. Use when a skill needs grounded pre-action option-space constraints.

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Processamento escalável de dados para workloads de ML. Execução em streaming em CPU/GPU, suporta Parquet/CSV/JSON/imagens. Integra-se com Ray Train, PyTorch, TensorFlow. Escala de uma única máquina para centenas de nós. Use para inferência em lote, pré-processamento de dados, carregamento de dados multi-modal ou pipelines distribuídos de ETL.

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Use this Canvas-owned clean-room skill when a spreadsheet file is the primary input or output. Trigger for `.xlsx`, `.xls`, `.xlsm`, `.csv`, `.tsv`, workbooks, templates, trackers, models, dashboards, charts, formulas, data cleaning, formatting, validation, recalculation, and Google Sheets-targeted handoff.

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飞书云空间（云盘/云存储）：管理云空间（云盘/云存储）中的文件和文件夹。上传和下载文件、创建文件夹、复制/移动/删除文件、查看文件元数据、管理文档评论、管理文档权限、订阅用户评论变更事件、修改文件标题（docx、sheet、bitable、file、folder、wiki）；也负责把本地 Word/Markdown/Excel/CSV/PPTX 以及 Base 快照（.base）导入为飞书在线云文档（docx、sheet、bitable、slides）。当用户需要上传或下载文件、整理云空间（云盘/云存储）目录、查看文件详情、管理评论、管理文档权限、修改文件标题、订阅用户评论变更事件，或要把本地文件导入成新版文档、电子表格、多维表格/Base/幻灯片 时使用。"云空间"、"云盘"和"云存储"是同一概念，用户说"云盘"、"云存储"、"网盘"、"我的空间"时均路由到本 skill。当用户给出 doubao.com 的云空间资源 URL/token，或明确提到豆包里的 file/folder/docx/sheet/bitable/wiki 资源时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是资源类型、URL 路径模式和 token，而不是域名。

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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Use this skill when a company has a risk assessment and treatment plan and now needs its first statement of applicability, and asks "build our SoA", "draft the statement of applicability", "which controls apply to us", "SoA from the risk treatment plan", "justify inclusions and exclusions" or "our SoA says implemented everywhere". Drafts one row per control of the reader's framework with the inclusion decision, the risk or obligation behind it, an implementation status taken from records, an evidence pointer and an owner role, and writes a CSV statement plus notes of open decisions.

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Use this skill when a team needs its first information security risk register, or has one that is a copied catalogue nobody owns, and asks "build our risk register", "draft a risk assessment", "what are our top risks", "risk register from scratch", "our auditor wants a risk assessment" or "turn our incidents and findings into risks". Drafts 20 to 40 company-specific risk scenarios from the material the agent can reach, scores them against an agreed method, proposes owners and treatments, and writes a CSV register plus a notes file of assumptions and questions for owners.

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Use this skill when a risk register has treatment decisions but no plan anyone can execute, or when someone asks "write the risk treatment plan", "turn the risk register into actions", "what do we do about our high risks", "treatment plan for the auditor", "budget the security roadmap from the risks" or "our treatment plan is just a list of controls". Turns each reduce, avoid or transfer decision into dated actions with an owner, budget, dependency and the record that will prove it was done, states the expected residual score and why, and adds interim measures for risks that stay high while the work runs. Writes a CSV plan and a short notes file.

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Use this skill when a company needs to know what AI it builds, buys or uses, before an AI governance programme, an AI regulation review or a customer questionnaire, and asks "list our AI systems", "build an AI register", "AI inventory", "where are we using AI", "find shadow AI", "which of our vendors use AI" or "what AI do we have before the AI Act". Discovers AI systems from procurement, single sign-on, code and teams, records one entry per use case with owner, purpose, data, affected people and the company's role, and writes a CSV register plus notes of borderline cases and open questions.

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Create, revise, and validate publication-ready academic paper figures and tables. Use for LaTeX tables, related-work comparison tables, result tables, notation/dataset/taxonomy tables, precise source-data-driven experiment plots from CSV/JSON/logs, generated conceptual figures such as system overviews/pipelines/architectures/threat models, captions, artifact specs, source-data traceability, and paper-ready PDF/SVG/PNG/LaTeX exports. Do not use for prose-only paper writing, self-review, reviewer response, rebuttal drafting, or external literature-management workflows.

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Use Exasol `IMPORT` and `IMPORT INTO` SQL plus `exapump upload` local file workflows for moving data into Exasol. Covers CSV, FBV, and Parquet, `CREATE CONNECTION` connection objects for import, cloud credential patterns for S3, Azure Blob Storage, and Google Cloud Storage (GCS), reject handling, and staging-based import workflows. Native IMPORT does not read Avro, ORC, or Delta — those object-storage formats need the Cloud Storage Extension instead.

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Prepares the trend update for a recurring emailed report: identifies report emails not yet processed, extracts the configured metrics from their spreadsheet, CSV or PDF attachments, returns new rows for an append-only trends sheet and writes a DRAFT summary with period-on-period deltas and flagged anomalies. Use when the user asks to "update the trends for the weekly report", "analyse the latest monthly report", "what changed in the latest report", "do the latest numbers look unusual" or "set up tracking for a report that arrives by email". Do not use for a single file with no trend state, use dataset-insight-pack instead. Drafts for human review; never approves, authorises or signs off.

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Reads a purchase order extract (spreadsheet, CSV or pasted table) and returns a DRAFT question sheet for the buyer: possible split orders, round amounts, amounts just under an approval threshold, first-seen or near-duplicate vendors, duplicate orders and missing or self approvals, each a neutral question naming the PO numbers, never a finding. Use when the user asks to "review these purchase orders", "screen the PO log", "spot anomalies in this spend extract", "sanity-check the PO register" or "prepare buyer questions before the audit". Do not use for an expense claim or travel request checked against policy, use expense-policy-precheck instead. Drafts for human review; never approves, authorises or signs off.

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Reads a contract list (spreadsheet, CSV or pasted table) and returns a DRAFT renewal radar: each active contract's end date, notice deadline with its arithmetic, days remaining, renewal type, owner and the decision it needs as options, sorted by urgency, with owner action lists and a deadline calendar. Never renews, terminates, serves notice or recommends. Use when the user asks to "build a renewal tracker", "tell me what comes up for renewal", "work out when notice is due", "show me which contracts auto-renew" or "run the quarterly contract review". Do not use for reviewing one contract's full text or clauses, use contract-review-pack instead. Drafts for human review; never approves, authorises or signs off.

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Finds high-value SEO and GEO keywords using web search, AI analysis, and optionally paid tools like Ahrefs or Semrush. Produces a validated keywords.csv file with a fixed schema for downstream pipeline consumption.

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Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.

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Office Scripts (Excel Online / Microsoft 365) development expert skill. Covers platform limitations, ExcelScript API patterns, testing strategy (lib + Vitest), and 13 real-world bug patterns discovered during production development. Trigger words: Office Scripts, ExcelScript, Excel Online, Office Script development, TypeScript Excel, Excel automation, CalculateRequirements, ImportCsvData

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This skill should be used when analyzing bug ticket data to identify quality trends, assess software quality status, and provide improvement recommendations. Use when a user provides bug lists (CSV, Excel, JSON, or Markdown format) and needs comprehensive quality analysis from a QA manager perspective. Generates statistical analysis, identifies quality hotspots, provides actionable recommendations, and produces professional Markdown reports suitable for project managers and executive leadership. Ideal for IT system development, migration, and implementation projects.

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Discover and normalize entities for programmatic SEO from a seed keyword or CSV file. Writes normalized entities to data/entities.json. Use when the user wants to find, import, or expand a list of SEO targets.

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Create, read, edit Excel .xlsx spreadsheets and CSVs.

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Extract structured data from receipts and invoices for bookkeeping, expense tracking, and tax preparation. Supports email, photos, scanned images, PDFs, and accounting exports. Outputs vendor, date, amount, tax, line items as table, CSV, or JSON. Trigger on "process receipts", "extract receipts from email", "scan invoices", "capture expenses".

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