✨ A cheerful add-on kit for Hermes Agent · MIT licensed

Give your agent a memory, a map, and a health plan.

Long agent sessions bury their best clues in scrollback. Harness Plus keeps the receipts: Task Canvas evidence trails, local semantic recall, and share-ready skills — all optional, all local-first. 🧸

7+pluggable pieces 🧩
100%local-first 🏠
0changes to Hermes core 🪶
MITdo-what-you-love license 📜
🪦 The scrollback graveyard

Your agent works hard.
Its best clues deserve better than line 4,000.

A tool call surfaces the golden hint. A test log answers the big question. Ten minutes later, it's all buried — and everyone pays for it.

😵‍💫

Forgotten clues

The crucial output scrolls away, and the session quietly loses the shape of the work.

🔁

Repeated dead ends

Without a map of what failed, the agent happily tries the same broken path again.

🤷

Unverifiable answers

"Trust me" is not a citation. Final answers should point back to real evidence.

🎁 What's in the box

Seven little helpers, one happy harness.

Every piece is optional and independent. Take one, take all — Hermes Agent itself is never modified.

🗺️

Context Canvas

A tiny library that keeps short JSON nodes plus evidence refs — so every finished note has a path back to the facts.

Read the origin story →
🛰️

Canvas MCP sidecar

Native MCP tools for Hermes: canvas_start, canvas_add_ref, canvas_search, canvas_closeout and friends.

🤖

Autopilot plugin

Caches full sanitized tool results, then adds only failures, verifications, and state changes to the map. Fail-open, never edits conversation history.

🔎

Qdrant recall kit

Index selected skills and recent sessions into your own local Qdrant — with dry-run previews and secret-pattern redaction.

🩺

Recall watchdog

Scheduled health checks that stay quiet on green and get specific on failure — plus bounded Docker restart helpers.

📚

Skills & checklists

Drop-in Hermes skills and ops checklists that teach the habits: keep the map, find it again, share cleanly.

🧭

Delegation calibrator

Optional complexity × Bayesian evidence for direct versus luna_max — with Baton and the main agent still in charge of judgment.

Read the routing guide →
⚡ Quick start

From zero to first canvas in about a minute.

Three copy-paste steps. The full install guide covers MCP wiring, the autopilot plugin, and Qdrant helpers.

Grab the toolbox

Clone the repo and hop in.

# clone & enter git clone https://github.com/phenomenoner/\ hermes-agent-harness-plus.git cd hermes-agent-harness-plus

Prove it works

Install and run the smoke tests.

# install + smoke tests python -m pip install -e '.[mcp]' pytest python -m pytest -q

Start a canvas 🎉

Give your first task a memory.

# first Task Canvas PYTHONPATH=packages/context-canvas \ python -m context_canvas.cli start \ --session-id demo \ --goal "Keep evidence for a long task"
🧭 Our promises

Cute on the outside, careful on the inside.

🏠 Local-first — your data stays home 🪶 Zero changes to Hermes core 🛟 Fail-open — helpers never block your session 🔍 Dry-run previews before any indexing 🧾 Every claim links to evidence
💬 Tiny FAQ

Good questions, honest answers.

Does it modify Hermes Agent?

Nope! Everything is an optional outer layer — adapters, plugins, sidecars, skills, and checklists. Remove any piece and Hermes keeps running exactly as before.

Where does my data go?

Nowhere. Canvases live under ~/.hermes/context-canvas, and Qdrant recall binds to 127.0.0.1 by default. Session indexing skips system prompts and tool outputs, redacts common secret patterns, and always supports --dry-run previews.

Do I need all seven pieces?

Not at all — they're independent. Lots of value starts with just the Task Canvas CLI. Add the MCP sidecar, autopilot plugin, Qdrant recall, or the optional delegation calibrator whenever your workflow asks for them.

What do I need to run it?

Python 3.10+, plus a working Hermes Agent install for the MCP and plugin pieces. The Qdrant helpers want a local Qdrant (Docker works great) and fastembed. Details live in the install guide.