hermes-bridge
Skill1 starsChanged 32 days agoMITView on GitHub
Instructions for the upstream workflow: Expose auto_route/local_chat/fusion/find_skills/infra_tips to Hermes-Agent (or any framework that expects OpenAI-function-calling tool specs instead of MCP) — plus a one-call MCP config generator for the zero-code path if the framework already speaks MCP. Use when connecting the toolkit's routing belt to another agent framework.
2 other projects use a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- zedarvates/botte-secreteedited, first seen Aug 8, 2026
- Fighter90/career-ops-uitheir own version, first seen Jun 27, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 1
- zedarvates/botte-secrete★ 270% same
Wrote their own version · 1
- Fighter90/career-ops-ui★ 96same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository114 other files it gives its agents.
- agent-cacheSkill
- agent-compressionSkill
- agent-intelSkill
- agent-overlapSkill
- agent-stateSkill
- ambient-hudSkill
- app-testSkill
- audit-dagSkill
- auto-distillSkill
- auto-memorySkill
- auto-routerSkill
- benchSkill
- bootstrapSkill
- botte-learnSkill
- botte-nnSkill
- botte-proxySkill
- botte-wrapSkill
- cacheSkill
- call-chainsSkill
- capabilitiesSkill
- cardinalSkill
- checkupSkill
- clarificationSkill
- clusterSkill
- code-complexitySkill
- code-duplicationSkill
- code-fingerprintSkill
- code-rulesSkill
- code-stateSkill
- code-wrappersSkill
- comfyuiSkill
- completion-proofSkill
- conductorSkill
- context-budgetSkill
- context-compressorSkill
- context-profilerSkill
- context-slicerSkill
- context-windowsSkill
- control-loopSkill
- cost-estimatorSkill
- dag-optimizerSkill
- dashboardSkill
- decision-ladderSkill
- demoSkill
- diff-languageSkill
- directives-auditSkill
- docgenSkill
- docs-stewardSkill
- dynamic-workflowsSkill
- efficiencySkill
- eventsSkill
- fallow-likeSkill
- fallowSkill
- fast-contextSkill
- fixSkill
- fleetSkill
- hailo-visionSkill
- harness-deltaSkill
- harvestSkill
- hermes-second-brainSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 56
Every task [[hermes-second-brain]] would otherwise send straight to its own model gets a chance to resolve locally or via the cheapest …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
hermes-bridge — connect the belt to another agent framework
Package scope and prerequisites
This catalog ships instructions, not the executable runtime. Python modules, scripts, local services and optional tools named below must be installed separately from the upstream project. Check their availability before running commands; if they are missing, explain the prerequisite instead of claiming execution or results. The host agent may use model tokens while following these instructions.
the toolkit already runs a standard MCP server (skills.llm_mcp.server,
stdio JSON-RPC). If the target framework speaks MCP, that's the whole
integration — no code in this module runs:
python -m skills.hermes_bridge.cli config --cwd /path/to/project
# → paste the printed {"mcpServers": {...}} block into the framework's MCP configThis module exists for frameworks — [[hermes-second-brain]] among them — that instead expect a flat list of OpenAI-function-calling tool specs + a dispatcher, a common shape for agents built before/without MCP support.
python -m skills.hermes_bridge.cli schemas # the 5 tool specs, OpenAI-shaped
python -m skills.hermes_bridge.cli call botte_auto_route --prompt "rename x to y"from skills.hermes_bridge import TOOL_SCHEMAS, dispatch
# register TOOL_SCHEMAS with the framework's tool-calling mechanism, then:
dispatch("botte_auto_route", {"prompt": "..."}) # → JSON string, same shape as the MCP toolThe 5 tools
Deliberately a subset of the ~35-tool MCP surface — the ones that matter for a second-brain / routing integration:
| tool | what it does |
botte_auto_route | plan local-vs-cloud routing; execute=true to actually run it |
botte_local_chat | run a prompt on a configured local model; inspect usage and forwarding |
botte_fusion | cascade / draft_refine / vote — models collaborating |
botte_find_skills | 0-token local search over installed skill catalogs |
botte_infra_tips | hardware/software setup advice for running local models |
Why this matters for a second-brain agent
Every task [[hermes-second-brain]] would otherwise send straight to its own
model gets a chance to resolve locally or via the cheapest capable tier
first — see [[bench]] for how to measure it with a compatible runtime; no result is established by this catalog.
botte_find_skills also gives Hermes 0-token access to the local skill
catalog instead of re-deriving capabilities from scratch each session.
Related: [[llm-mcp]] (the native MCP server this bridges from), [[auto-router]],
[[bench]] (the proof), docs/integrations/hermes.md (the full integration write-up).
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

