'dedup' 검색 결과

Train sentence-transformers models for search, similarity, and reranking, which reorders search results by relevance. Choose a model type, prepare data, configure training, compare results against a baseline, and publish the trained model to Hugging Face Hub.

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• Fine-tuning an embedding model for domain-specific search
• Training a model to rerank search results
• Training SPLADE or ColBERT retrieval models

Research prospective customers from public sources, add company and contact details, score their fit, and merge duplicate records. Organize the findings into prioritized lead lists with source information, using CSV, JSON, or Markdown tables.

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• Find companies matching an ideal customer profile
• Add funding and hiring details to lead records
• Score prospects to set sales priorities

Organize Linear or Jira backlogs through the Composio CLI, a command-line tool. Fetch issues in bulk, group likely duplicates, update labels, priorities, and owners, then share a summary of changes in Slack.

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• Weekly reviews of unassigned or stale issues
• Post-release bug reviews and owner assignment
• Grouping duplicate reports and linking related issues

Review open issues and discussions to organize a project's backlog. Identify possible duplicates, suggest priorities and labels, and record the top five actionable items and cases needing human attention in a state file.

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• Organizing a growing issue backlog
• Selecting the top five actionable issues
• Suggesting labels and possible duplicates

Review open issues and discussions to create a clear work queue. Record the five highest-priority items, suggested labels, possible duplicates, and cases needing human judgment in a state file for future reviews.

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• Prioritizing a backlog of open issues
• Finding possible duplicate reports
• Preparing label suggestions

Train sentence-transformers models for search, similarity, and reranking, which reorders search results by relevance. Choose a model type, prepare data, configure training, compare results against a baseline, and publish the trained model to Hugging Face Hub.

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• Fine-tuning an embedding model for domain-specific search
• Training a model to rerank search results
• Training SPLADE or ColBERT retrieval models

Run a quick first review of code changes with six specialist agents working in parallel. They check logic, input and output, shared state, resources, missing behavior, and API completeness, then combine duplicate findings into a report ranked by confidence.

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• Running a quick first review of a patch
• Screening diffs to prioritize further investigation
• Checking for missing cleanup and handlers

Maintain data retention in ClawHub's Convex tables by classifying each table, defining expiration fields, and bounding cleanup jobs. Guide changes to temporary data and expired authentication records, with focused tests and runtime verification.

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• Classify retention policies for new tables
• Add expiration fields and indexed cleanup
• Update scheduled jobs with bounded deletion batches

Combine Convex authorization, code quality, performance, and failure audits into one readiness report. It removes duplicate findings, scores confirmed issues with a stated formula, and orders the fixes while clearly identifying checks that could not run.

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• Reviewing a Convex app before launch
• Combining audit findings into one report
• Prioritizing authorization and performance fixes

Turn rough meeting notes, customer requests, and product ideas into structured backlog entries, a list of possible improvements. Capture who needs each idea and why, categorize it, and update matching entries with new evidence.

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• Capturing feature ideas after a meeting
• Recording requests from customers or sales
• Logging product gaps found in competitor research

Add, extend, or review OpenAI Ads conversion tracking for purchases, signups, and other confirmed outcomes. The skill covers browser Pixel events, server-side Conversions API events, duplicate-event prevention, secret handling, and local verification with a setup report.

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• Add tracking for completed purchases and signups
• Send conversion events from a server
• Prevent duplicate counting across Pixel and CAPI

Draft and revise X posts in Meng To's voice using his authored posts and verified personal and product context. Generate distinct alternatives, check for repeated angles, and refine a reusable voice profile as new posts are collected.

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• Draft or revise posts in Meng To's voice
• Create replies, threads, resource shares, and quote posts
• Check whether a proposed angle repeats an earlier post

Write JavaScript for n8n Code nodes to aggregate, filter, and transform workflow data. Guidance covers data access, output formats, execution modes, common errors, and performance choices when processing large numbers of records.

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• Aggregating and deduplicating multiple records
• Transforming complex API responses
• Fixing data access and return format errors

Refactor C#/.NET code through renaming, extraction, consolidation, and other structural changes while preserving behavior. Check compatibility beyond code references, including public APIs and serialized names, then validate with builds and relevant tests.

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• Rename C# members and update their references
• Extract shared logic from duplicate code
• Reorganize code while preserving public API compatibility

Extract unidentified external addresses from TRES Finance and export a deduplicated Excel workbook. An import-ready contacts sheet lets users add names and tags, while a reference sheet shows inferred networks, transaction counts, and USD volumes to help prioritize labeling.

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• Building an address book from transaction history
• Preparing a TRES contacts import sheet
• Prioritizing unidentified addresses by transaction volume

Collect papers across research databases, turn research questions into targeted search queries, remove duplicate records, and extract available PDF links. Useful for preparing systematic literature reviews, with database selection and access checks before retrieval.

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• Collecting papers across multiple research databases
• Turning research questions into database search queries
• Removing duplicate records and finding PDF links

Find related research by following a paper's references and the later papers that cite it through Semantic Scholar. Filters prioritize relevant candidates, avoid duplicate reviews, and record citation relationships for a focused literature search.

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• Finding related studies from a relevant paper
• Checking which papers cite a study
• Tracing earlier work through references

Comprehensive citation management for academic research. Resolve bibliographic identifiers, extract accurate metadata, validate citations, deduplicate references, and generate properly formatted BibTeX entries. This skill should be used when you need to verify citation information, convert DOIs/PMIDs/arXiv IDs to BibTeX, or ensure reference accuracy in scientific writing.

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Use when operating PAIDF Curation and Retrieval or NVIDIA Cosmos Curator pipelines (split, filter, caption, embed, dedup, shard, image annotate) or PAIDF Data Mining nearest-neighbor matching on Curator embeddings. Activate for Make or CLI pipeline config, GPU run preflight, FFmpeg sidecar, SAM3 keys, or Curator-to-TAO handoff. Do not use for generic ETL, vector-database RAG, model training, orchestration, or embeddings outside Cosmos Curator and PAIDF Data Mining.

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Audit wiki health: broken links, orphans, contradictions, stale content, lifecycle and tag issues. Use for maintenance or health checks. Default is report-only; use wiki-dedup for page-identity merges.

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Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep includes UMIs and accurate molecule counting is needed, such as in single-cell RNA-seq, low-input RNA-seq, or targeted sequencing to distinguish PCR from biological duplicates.

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All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps.

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Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.

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Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub). Each iteration pops a seed from the queue, fetches sources, drafts a wiki page, dedupes claims against existing pages, enqueues follow-up seeds. Halts on budget cap, depth cap, or convergence. Use when the user says "research <topic>", "grow the <slug> wiki", "auto-research", or wants a knowledge base that builds itself overnight.

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