microsoft / microsoft/graphrag
[Feature Request]: Doc improvement, add a GraphRAG specific failure mode checklist and debug guide
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 36k
- Forks
- 3.8k
- Avg merge
- 20h 40m
- Merged PRs (30d)
- 4
Description
Do you need to file an issue?
- I have searched the existing issues and this feature is not already filed.
- My model is hosted on OpenAI or Azure. If not, please look at the "model providers" issue and don't file a new one here.
- I believe this is a legitimate feature request, not just a question. If this is a question, please use the Discussions area.
Is your feature request related to a problem? Please describe.
Hi maintainers,
GraphRAG pipelines introduce additional failure surfaces beyond classic RAG, such as entity linking errors, graph construction skew, path based retrieval collapse, and context assembly issues.
Proposal (doc only, minimal):
- A short “GraphRAG Failure Modes” checklist, focused on practical symptoms and quick checks
- A “Debug Playbook” section, example: entity mismatch, graph fragmentation, wrong path retrieval, missing grounding, overconfident generation
This is intended to help users debug faster and report higher quality issues.
If you like the idea, I can submit a PR with an initial doc page that follows your current documentation style.
Which directory would you prefer?
Describe the solution you'd like
No response
Additional context
No response
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the repository's existing documentation structure and style to determine where a GraphRAG failure-mode checklist and debug playbook belong. Done means adding a documentation page covering the proposed symptoms and quick checks, including entity mismatch, graph fragmentation, path retrieval, grounding, and overconfident generation.
Written by the indexing model from the issue text.
Assessment
- Domain
- ai, documentation
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- Half a day
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100