GPT-RAG Data Ingestion is a service that processes documents such as PDFs, images, spreadsheets, transcripts, and SharePoint files so they can be searched through Azure AI Search. It prepares data with format-specific chunking and text or image embeddings for multimodal retrieval in agent-based applications.
Borrowing it
Nothing to install: this file belongs to Azure/gpt-rag-ingestion. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Azure/gpt-rag-ingestion/main/.github/skills/service-release/SKILL.mdgit clone --depth 1 https://github.com/Azure/gpt-rag-ingestionWrote 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/azure/gpt-rag-ingestion/service-release)<a href="https://agentmods.dev/skills/azure/gpt-rag-ingestion/service-release"><img src="https://agentmods.dev/badge/skills/azure/gpt-rag-ingestion/service-release/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/azure/gpt-rag-ingestion/service-release"><img src="https://agentmods.dev/badge/skills/azure/gpt-rag-ingestion/service-release.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 | $0.00042 | $0.00339 |
| Opus 5 | $0.00021 | $0.00169 |
| Sonnet 5 | $0.00008 | $0.00068 |
| Haiku 4.5 | $0.00004 | $0.00034 |
Grade A, and why
service-release 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 11d 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
Ingestion service release
Read .github/copilot-instructions.md completely before changing a release
artifact.
- Determine the intended semantic version and create
release/x.y.zfromdevelop. - Set root
VERSIONtox.y.zwithoutv. - Replace the staged
## [Unreleased]heading with## [vX.Y.Z] - YYYY-MM-DD; do not add a newUnreleasedsection on the release branch. - Verify branch,
VERSION, changelog, Git tag, and GitHub Release title are synchronized. - Identify the compatible Azure/GPT-RAG umbrella and component versions and validate the exact ingestion commit or image in that context.
- Record Python, frontend, container, and controlled Azure evidence required by the changed behavior.
- Confirm documentation status and rollback or roll-forward steps.
- Target the release pull request to
main. - After merge, create exactly
vX.Y.Zfor the tag and release title only with explicit human approval. - Re-fetch the release and verify formatting and the absence of private Azure environment or resource-group names.
After the release, recreate the empty Unreleased section separately on
develop. Report incompatible contracts, missing validation, or
documentation drift as blockers rather than filling gaps by assumption.
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.
- 11d ago First seen · 33 lines · 42 tokens per session scan A bae4af9bd977
service-release is a skill published in the GitHub repository Azure/gpt-rag-ingestion (189 stars, last pushed 2d ago), licensed MIT. It adds 42 tokens to every session and 339 once invoked, about $0.0002 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
agent-release-swarm
Agent skill for release-swarm - invoke with $agent-release-swarm.
release-announcement
Write a release announcement — changelog, blog post, in-app note, or social post — that leads with user impact, names the audience, and includes upgrade/migration steps without filler.
multi-agent-release-manager
Cleans up the workspace, formats code, runs presubmit checks, and uploads CLs to Gerrit.
release-notes
Generate user-facing release notes from tickets, PRDs, or changelogs. Creates clear, engaging summaries organized by category (new features, improvements, fixes). Use when writing release notes, creating changelogs, announcing product updates, or summarizing what shipped.
pack-submit
Package one of this agent's own skills as a standalone community pack and submit it to the aeon registry as a PR.
updater_guide
Guidance for checking for and installing Row-Bot updates.