Research: current AI discoverability evidence
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Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 35/100
- Issue type
- Documentation
- Clarity
- Mostly clear
- Activity status
- Active
- Domain
- documentation
Research direction
Read parent issue #1159, hook #1107, and the referenced SPEC.md to establish the scope and evidence standard. The issue calls for sourced research in docs/research/ on llms.txt, JSON-LD, documentation, and MCP, with each claim traceable to a specification or issue. Refine the stub and agree on scope before starting; done means the findings distinguish honest tactics from manipulative ones and contain no hidden text, prompt injection, or fake endorsements.
Written by the indexing model from the issue text.
Description
Part of #1159.
Outcome
Gather sourced findings into docs/research/ on what answer engines and agents actually use (llms.txt, JSON-LD, docs, MCP), with rules separating honest tactics from manipulative ones.
Hooks
#1107
Notes
- Honest tactics only: every claim traces to SPEC.md or an issue; no hidden text, prompt injection or fake endorsements.
- Stub: refine before work starts.
- Dominant language
- Python
- Stars
- 1
- Forks
- 0
- Avg merge
- 2d 5h
- Merged PRs (30d)
- 43
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing 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.
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