'ingest' 검색 결과

Re-ingest-correctness SOP for production RAG. Activate when a calling agent builds, reviews, or debugs an ingestion pipeline that runs more than once over a changing corpus — scheduled re-index, incremental updates, CI re-ingest, or a "retrieval has duplicates / shows deleted docs" bug. Encodes the rule — **ingestion must be idempotent: a document's content hash decides insert/update/skip, so re-running over unchanged docs is a no-op** — plus the docstore + doc-hash upsert machinery (LlamaIndex `IngestionPipeline` + `DocstoreStrategy`), the delete-propagation problem, and cross-framework equivalents (LangChain `index()` + `RecordManager`, manual hash table). ENHANCE overlay over [[llamaindex]]: the IngestionPipeline exists in the base skill but the re-ingest-correctness contract is not surfaced.

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Helps developers send conversion and event data to Google Ads, Google Analytics, and Floodlight through the Data Manager API. It covers destination setup, data formatting, validation, migration from other APIs, and checking processing results.

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• Implement offline conversion uploads to Google Ads
• Send recommended or custom GA4 events
• Migrate event ingestion from another Google API

Turn supplied text, files, or approved URLs into linked Obsidian notes with source records and evidence tracking. Review proposed changes before applying them, preserve original materials, and record contradictions or gaps in support.

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• File research materials with their sources
• Connect new sources to existing notes
• Track conflicting claims and missing evidence

Ingest supplied source material into an Obsidian vault with provenance and claim tracking: pasted text, files staged in the selected vault's inbox or .raw archive, or explicitly approved URLs. Use for a single source or bounded batch, not for saving an assistant answer. Triggers: ingest, ingest this file, ingest this URL, process this source, read and file this source, batch ingest, ingest these sources.

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Open-format data ingestion for NV oOS Pro toolkits — the reusable pattern behind the F&B data-ingestion track (Proposal 078). Covers structural (header) matching over filename mapping, the configurable table_map + header-matcher + name-guess resolution order and the slug-first regression, the multi-format loader (CSV/TSV/JSON/JSONL/XLSX/ODS/PDF/photo), the Observation + terminology-map layer (vitals/FHIR analogue) with raw preservation, dedupe/retention/out-of-band banding, complete-by-default/resumable (offset) imports, and the read-only ingest-review dashboard anatomy (edit_posts review vs manage_options write, dry-run-first). Use when adding or extending data ingestion to a toolkit, ingesting heterogeneous owner files, wiring XLSX/PDF/photo imports, building an ingest/review dashboard, or debugging partial/truncated imports.

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Convert a research paper into structured files covering its problem, claims, concepts, experiments, and figure or table evidence. Validate the generated directory, ingest it into OpenViking, and check that the target resource was created.

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• Import a paper PDF into OpenViking
• Organize a paper's claims and experimental evidence
• Preserve figures and tables as evidence files

Tune cognee ingestion speed, query response time, and LLM costs by adjusting concurrency, text chunk sizes, request limits, and model choices. Estimate ingestion costs before processing and assess options for background work and deployment scaling.

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• Estimating costs before importing documents
• Adjusting ingestion speed and request limits
• Reducing query response time

Collect public posts across a blog, newsletter, or feed archive and save clean Markdown pages for each article. The workflow avoids duplicates, supports resumed runs, repairs empty results, and hands articles to a separate enrichment skill.

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• Importing a blog's public article archive
• Organizing public newsletter posts as knowledge pages
• Rerunning a feed import without duplicates

Turn videos, audio, PDFs, books, screenshots, and GitHub repositories into knowledge pages with summaries and highlights. Preserve original files, extract people and companies, and connect the material to their pages and timelines for later reference.

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• Saving key points from YouTube videos or podcasts
• Organizing PDF and book summaries by subject
• Extracting text and entities from screenshots

Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API. Triggers: "azure-monitor-ingestion", "LogsIngestionClient", "custom logs", "DCR", "data collection rule", "Log Analytics".

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Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).

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Ingest raw sources into the structured wiki — "ingest", "add this to my wiki", new files in raw/, clippings, sources, ideas, nightly ingest. Produces pages with YAML frontmatter and a mandatory Counter-Arguments section.

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저장된 자료를 읽어 LLM Wiki의 출처, 인물·조직, 개념, 종합 지식 페이지로 정리합니다. 상호 링크와 색인, 수집 이력을 갱신하고 기존 정보와의 모순을 기록합니다.

• 저장된 자료를 LLM Wiki에 추가
• 인물·조직과 개념 정리
• 기존 정보와의 모순 기록

Check names, aliases, and existing pages before saving content to a gbrain knowledge store. The skill reads likely matches to identify duplicates, links to existing information, and routes new material to the appropriate ingestion skills.

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• Check notes for duplicates before saving
• Resolve different names for the same person or company
• Review files before a bulk import

Prepare a local development environment for the Data Manager API with authentication and library installation guidance. It covers five programming languages and companion utilities for formatting, hashing, and encrypting user identifiers before ingestion.

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• Preparing a local environment for the Data Manager API
• Installing client and identifier utility libraries
• Configuring local credentials and access scopes

Analyze Axiom data ingestion and query usage to identify unused columns and field values. Build cost dashboards and spike monitors, then summarize recommendations for dropping or sampling data with estimated savings.

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• Find unused data that contributes to Axiom costs
• Track ingestion trends and projected spending
• Set up alerts for ingestion and query cost spikes

Develop and troubleshoot plugins that connect external memory services to Nexent. Define plugin settings, implement search and ingestion, map errors, test with simulated network responses, and verify deployment, authentication, and runtime monitoring.

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• Adding an external memory service to Nexent
• Reviewing an existing memory adapter
• Testing plugins without live service connections

Extract clean Markdown from a web page URL using Defuddle. The skill provides a command example for an Obsidian source-ingestion workflow and identifies Sources/Web/ as the typical destination for web source material.

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• Extracting a web page as Markdown
• Preparing web material for Obsidian ingestion
• Using Sources/Web/ as a destination for web sources

Ingest new documents, raw text, folders, or URLs into the Obsidian wiki as distilled, linked knowledge. Use for general wiki ingestion when no more specific ingest skill applies, including processing _raw/ staged content.

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Route generic agent-history ingestion requests to the appropriate specialized history-ingest skill. Use when the user asks to ingest AI-agent history without directly selecting the underlying agent-specific skill.

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Azure Monitor Ingestion SDK for Java. Send custom logs to Azure Monitor via Data Collection Rules (DCR) and Data Collection Endpoints (DCE). Triggers: "LogsIngestionClient java", "azure monitor ingestion java", "custom logs java", "DCR java", "data collection rule java".

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Synthesize raw recon/test output into engagement state. Reads everything dropped in targets/<active>/ingest/, extracts hosts/assets/creds/paths, merges into state.md/loot.md/Killchain.md, logs it, archives the raw files. Works for pentest, bugbounty, and ctf. Use when asked to "ingest", "synthesize findings", "process recon", or after dropping tool output in the ingest folder.

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Close out a review/meta branch that lands an evidence-ingest / curation batch: create the named nodes, ingest verified evidence, appraise Trust Magnitude, calibrate stars, wire suites, correct upstream naming, stage ONLY the intended artifacts (dropping CRLF churn and blocking leaks), validate, and open the PR. Use when a curation/ingest batch is verified and ready to land, or when the user says "close the review/meta branch", "land the ingest batch", "wrap up the intake PR", "/gaia-review-meta-close". Wraps the deterministic hygiene in scripts/review_meta_close.py and gates the judgment calls (calibration, Origin, suite promotion, naming, merge) behind explicit human checkpoints.

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Atomically ingest one already-verified evidence row into one named Gaia skill using the CLI, then appraise Trust Magnitude and propose—never silently apply—a calibration. Use after /ev-pipeline has verified an approved intake source, or whenever a curator says "ingest evidence", "add verified evidence", "gaia-ingest", or "turn this source into registry evidence".

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