effortless-hermes

A Hermes port of HeyCubit/effortless (MIT): a fast judge reads each prompt once per turn and picks the reasoning effort for it — easy questions run cheap, hard jobs get high — by rewriting the LLM request before it ships.

How it works

• An llm_request middleware fires once per user turn (keyed on turn_id), reads the next user message plus recent context, asks a judge, and rewrites every reasoning-effort carrier already present in the provider kwargs (reasoning_effort, extra_body.reasoning.effort, reasoning.effort). It never invents a carrier a provider doesn't use, never touches messages, and never changes the model — so the prompt-cache prefix stays intact.
• On a retried request within the same turn the cached verdict is reapplied.
• A named level in the message ("max effort", "effort: high") wins without a judge; a short follow-up ("go", "ok") keeps the current effort; a judge that is unsure (<0.5) or down falls through to the fallback judge, and if that fails too the current effort is kept.
• Verdicts are logged (last 50) in profile-scoped plugin state and shown by /effortless in interactive sessions.

Judges

Backend	Config	Notes
jev (default)	typesafe_key setting (stored as EFFORTLESS_HERMES_TYPESAFE_KEY in .env), or the shared TYPESAFE_API_KEY env var	TypeSafe systemone, ~0.3 s, returns confidence
local (default fallback)	local_base_url (default http://127.0.0.1:8080/v1), local_model	any OpenAI-compatible server; must be running
custom	custom_base_url, custom_model, custom_api_key (stored as EFFORTLESS_HERMES_CUSTOM_API_KEY in .env)	any OpenAI-compatible API

Secrets are read only through Hermes' profile-scoped secret store (agent.secret_scope), never from .env files or os.environ directly. When no key is set, the jev judge is skipped and the fallback chain runs; when nothing answers, the current effort is kept — the plugin never blocks a prompt.

Settings (plugins.entries.effortless-hermes.settings in config.yaml)

enabled (bool, true) · judge_backend (jev|local|custom) · fallback_backend (local|custom|jev|none) · judge_timeout_seconds (3.0) · effort_floor (low) · effort_ceiling (max) · effort_bias (-2..+2) · judge connection keys per the table above.

Commands

• /effortless — show the last verdicts
• /effortless test — send a sample prompt through both judges

Security disclosure

• Network calls: with the default config the plugin sends your next message (up to 4000 chars) and a short excerpt of recent conversation (up to 1600 chars) to https://api.typesafe.ai/v1/systemone (TypeSafe Jev) on the first request of each turn, solely to pick the effort. The local backend sends the same text to the base URL you configure (default 127.0.0.1:8080); the custom backend to your configured API. No other data leaves the machine; there is no telemetry, no usage reporting, no file access beyond the plugin's own state.
• Latency budget: each judge is bounded by judge_timeout_seconds (default 3 s; local and custom judges allow up to 8 s). A judge that hangs is abandoned, not awaited.
• Credentials: keys come from the settings hub (stored in Hermes' .env) or the TYPESAFE_API_KEY env var, resolved through agent.secret_scope.get_secret so profile-scoped secrets stay scoped. The plugin never reads .env files itself and never writes credentials anywhere.
• Code: pure-stdlib Python (urllib), no pip dependencies, no shell-outs, no background processes, no self-updating code.

Verified

• 2026-10-14, Hermes v0.21.7, glm-5.3 via surplusintelligence: "What day comes after Tuesday" → reasoning_effort: low in the live request dump (jev, 99% sure, 331 ms); "Refactor the entire auth system…" → high (82% sure); retry reapply confirmed via double dumps; hermes plugins validate --install-deps clean.

Not in v0 (deliberate)

Per-prompt model routing (effortless keeps it off by default too), the desktop status bar UI, the cache-countdown timer, handoff/compact triggers, and Anthropic thinking budget carriers (providers without a text effort carrier are skipped, never guessed).

License

MIT. Judge prompts and heuristics adapted from HeyCubit/effortless (MIT).