hermes-agent/hermes
https://github.com/hermes-agent/hermes · revision 0123456789ab
Introduction
- Hermes Agent is a multi-gateway automation agent with a skill and tool system.
- It targets operators wiring language-model agents into chat and workflow platforms.
Scores
The Assay Score never replaces its dimensions, and Potential is a separate forward-looking indicator.
- Project Substance90
- Originality72
- Engineering Rigor86
- Open Source Readiness84
- Maintenance Health83
- Potential80
Evidence
Every record below is graded, revision-pinned, and citable by the scores above.
Repository snapshot (1)
evidence:repository:snapshotcomplete · grade A
Files (2)
evidence:file:src-agent-tscomplete · grade A
evidence:file:src-gateway-tscomplete · grade A
Repository features (4)
evidence:feature:readmecomplete · grade B
evidence:feature:licensecomplete · grade B
evidence:feature:cicomplete · grade B
evidence:feature:security_policycomplete · grade B
Similar projects
A one-depth functional cohort. Similarity measures comparability, not quality, and never implies misconduct. Popularity is context only.
other-org/autopilot
78% similar · confidence 75%
Selected because of problem overlap, feature overlap, technical similarity
This project only: json output
Candidate only: web dashboard
other-org/chatops-bot
62% similar · confidence 60%
Selected because of problem overlap, feature overlap, structural similarity
This project only: json output
Candidate only: web dashboard
other-org/task-runner
50% similar · confidence 40%
Selected because of problem overlap, technical similarity
This project only: json output
Candidate only: web dashboard
Additional candidates (1)
- other-org/adjacent-tool30% similar · confidence 40%
Cite this result
The badge states the engine profile, score, and provisional, stale, or insufficient-evidence state, and links back to this engine-specific result.
Prefix the badge and result paths with the deployment origin when embedding in a remote README.
Warnings and limitations
repository_code_not_executed
Assay evaluates the project, not its authors or their use of AI-assisted development tools. Scores are dimensioned, versioned, and grounded in cited evidence.