「extraction」の検索結果

Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is "the label's information is not in the features", (3) reviewers propose construct splits (e.g. "designation vs record-evident"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is "partially unpredictable" when the model was simply never shown the document the annotators read.

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Use when behavior-preserving frontend refactoring focuses on legacy OO hierarchies, subtype responsibilities, superclass extraction/collapse, or delegation, and the selected technique needs family-specific mechanics, risks, and JavaScript/TypeScript/React/Vue adaptation.

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Use when restructuring existing frontend code while preserving observable behavior, including responsibility extraction, module movement, conditional simplification, API cleanup, or data organization. Do not use for new feature behavior, behavior-changing bug fixes, dependency or framework migrations, or proven dead-code cleanup.

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Query the UCSC Genome Browser REST API to retrieve regulatory tracks, DNA sequences, cCRE annotations, TF binding clusters, and track schemas for any genomic region. Use when the user wants to look up what regulatory elements exist at a genomic locus, retrieve DNA sequence under peaks, query ENCODE cCREs or TF rPeak clusters from UCSC, check what tracks are available for a genome assembly, get chromatin accessibility across cell types, or cross-reference ENCODE data with UCSC-hosted annotations. Also use when the user mentions UCSC, genome browser, cCRE lookup, SCREEN, TF binding clusters, DNA sequence retrieval, or track data extraction.

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Create, run, and maintain API test collections using Bruno (OpenCollection YAML format and legacy Bru format). Use when the user wants to: (1) create a Bruno API test collection from scratch or from OpenAPI/Swagger specs, (2) write API request files with tests and assertions, (3) run API tests using bru CLI, (4) generate test reports (HTML, JUnit, JSON), (5) set up CI/CD pipelines (GitHub Actions) for automated API testing, (6) debug or fix failing Bruno API tests, (7) add environment configurations for API testing, (8) chain API requests with data extraction, or (9) work with any .yml/.bru Bruno collection files. Triggers on mentions of 'Bruno', 'bru CLI', 'API testing collection', 'OpenCollection', or requests to automate API testing with file-based collections.

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Systematic contract review assistance — clause extraction, risk flagging, and comparison — use when analyzing agreements.

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NLP on clinical text — de-identification, concept extraction, phenotyping from notes, and LLM safety guardrails.

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Pick, convert, and manage colors with format conversions, palette extraction, and harmony tools.

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Convert any pile of documents (PDF, Word, HTML pages, wiki exports, PowerPoint slides) into clean, LLM-ready markdown context: inventories the sources, picks the right extractor per file type (pdftotext or PyMuPDF for PDF, pandoc or mammoth for docx, readability extraction for HTML.

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Evaluate survey data pipelines and research methodology. Analyzes response bias detection (speeders, straight-liners, bots), statistical significance testing (t-test, chi-square, ANOVA with Bonferroni correction), sentiment and theme extraction from open-ended responses.

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Audit a resume builder or optimization tool for ATS compatibility, keyword matching accuracy, formatting standards, achievement quantification, skill extraction, and job-description alignment scoring. Use when reviewing resume software, career platforms, applicant tracking integrations, CV generators, or job application tools.

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Audit e-discovery and litigation document review systems -- data collection pipelines (PST, MBOX, SharePoint, Slack), document processing (OCR via Tesseract/ABBYY, metadata extraction, deduplication), Technology Assisted Review (TAR 1.0/2.0/CAL with recall/precision tracking).

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Audit contract management codebases for clause extraction accuracy, obligation tracking completeness, risk scoring model quality, renewal management, SLA monitoring, liability exposure, force majeure handling, and IP assignment detection..

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Extract, suggest, and sync tags and categories for blog posts across all major CMS platforms. Supports WordPress REST API, Shopify GraphQL, Ghost Content API, Strapi REST/GraphQL, and Sanity GROQ. Generates tag suggestions from content analysis (keyword frequency, heading extraction, semantic grouping), enforces minimum post-count thresholds to prevent thin tag archives, and syncs taxonomy via authenticated API calls. Use when user says "tags", "categories", "taxonomy", "tag suggestions", "sync tags", "WordPress tags", "Shopify tags".

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Restructure code while preserving behavior. Use for extraction, consolidation, ownership moves, or cleanup where verification must bracket structural edits.

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Translates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to Google Cloud BigQuery. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.

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Refactor messy Pharo code safely through the genie MCP tools, working from the live image (no files). Use for renames, method extraction, moving behavior, or general cleanup of existing code.

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Use when configuring or operating the native Salesforce Data Export Service (Setup → Data Export) — weekly or monthly CSV export, attachment inclusion, file-size split, the 48-hour download window, and the gap between this free utility and the paid Salesforce Backup and Restore product. Triggers: 'data export service', 'weekly export', 'export attachments', 'data export 48 hour download', 'data export missing objects', 'is weekly export a backup', 'bulk api 2.0 query job export', 'data loader extract batch', 'process-conf.xml export', 'incremental export systemmodstamp', 'export inventory retention owner'. NOT for the paid Salesforce Backup and Restore product (use that as a separate tool), NOT for Bulk API extraction (use data/bulk-api-patterns), NOT for HA/DR architecture (use architect/ha-dr-architecture).

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Team-wide charter and history optimization through skill extraction

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Use automatically for PDF tasks, including Chinese requests like 查看PDF, 读取PDF, PDF里写了什么, 总结PDF, 分析PDF, 提取PDF文字, 识别PDF内容, or questions about any .pdf file. Prefer text extraction with pdfplumber/pypdf first, then render pages with Poppler when layout, images, tables, stamps, watermarks, or scanned content matter.

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Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses.

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[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1; route continuous learning, session learning, and pattern extraction requests to continuous-learning-v2.

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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

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Compare two local documents and convert differences into LLM-ready Markdown in one synchronous call. Supports PDF, Word, PPT, and image documents accepted by Calliper, and returns a structured markdown diff table suitable for change review, clause comparison, downstream extraction, and rule-based validation.

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。