Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add opensearch-project/opensearch-agent-skills --skill ingestgit clone --depth 1 https://github.com/opensearch-project/opensearch-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/opensearch-project/opensearch-agent-skills/ingest)<a href="https://agentmods.dev/skills/opensearch-project/opensearch-agent-skills/ingest"><img src="https://agentmods.dev/badge/skills/opensearch-project/opensearch-agent-skills/ingest/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/opensearch-project/opensearch-agent-skills/ingest"><img src="https://agentmods.dev/badge/skills/opensearch-project/opensearch-agent-skills/ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00074 | $0.00378 |
| Opus 5 | $0.00037 | $0.00189 |
| Sonnet 5 | $0.00015 | $0.00076 |
| Haiku 4.5 | $0.00007 | $0.00038 |
Grade A, and why
ingest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Ingest
Category skill for local document processing — turning unstructured files into search-ready JSONL chunks.
Skills
| Skill | Description |
|---|---|
| document-processing | Process PDF/DOCX/PPTX into JSONL chunks via Docling (local, no AWS needed) |
Not Covered
This skill covers local document processing only (PDF/DOCX → JSONL chunks). It does NOT cover:
- Cloud-scale ingestion via OSIS pipelines → see managed-ingestion-service
- Structured bulk-indexing (
_bulkAPI) - OpenSearch
_ingestprocessor pipelines (grok, date, set, script) - Log/metric shipping (Fluent Bit, Data Prepper, Logstash)
When to Use
Read document-processing/SKILL.md when:
- User has PDFs/documents and needs JSONL chunks
- User wants to evaluate chunk quality before ingestion
- User mentions Docling, document processing, chunking
For cloud ingestion (JSONL → OSIS → OpenSearch index), see cloud/managed-ingestion-service.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 43 lines · 74 tokens per session scan A 07492aec5077
ingest is a skill published in the GitHub repository opensearch-project/opensearch-agent-skills (52 stars, last pushed 10d ago), licensed Apache-2.0. It adds 74 tokens to every session and 378 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
markitdown
Convert heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.
azure-ai
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
doc-parse
A document parser that converts PDFs, PowerPoint files, spreadsheets, and Word files into structured Markdown with metadata and a confidence score.
edgeparse
Extract structured content from any PDF for AI agents, RAG pipelines, and Copilot Skills. Use this skill whenever the user wants to read, analyze, or reason about a PDF document; needs to feed document content to an LLM; mentions PDF extraction, parsing, or conversion; wants tables, headings, or bounding boxes from a…
opendataloader-pdf
A tool for extracting structured content from PDF files, such as text, tables, formulas, and scanned pages. It can produce Markdown, JSON with page positions, or HTML for use in search and AI document systems.
complex-doc-rag
Use when building a RAG pipeline that ingests PDFs, Excel, CSV, or images — especially when debugging silent data loss, choosing between OCR tools, or handling edge cases like scanned pages, merged cells, or embedded charts.