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docs(honcho): wizard cadence default 2, prewarm/depth + observation + multi-peer

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- cli: setup wizard pre-fills dialecticCadence=2 (code default stays 1
  so unset → every turn)
- honcho.md: fix stale dialecticCadence default in tables, add
  Session-Start Prewarm subsection (depth runs at init), add
  Query-Adaptive Reasoning Level subsection, expand Observation
  section with directional vs unified semantics and per-peer patterns
- memory-providers.md: fix stale default, rename Multi-agent/Profiles
  to Multi-peer setup, add concrete walkthrough for new profiles and
  sync, document observation toggles + presets, link to honcho.md
- SKILL.md: fix stale defaults, add Depth at session start callout
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Erosika 2026-04-18 12:45:04 -04:00 • committed by kshitij
parent 5f9907c116
commit 098efde848
4 changed files with 103 additions and 17 deletions
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8
optional-skills/autonomous-ai-agents/honcho/SKILL.md
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@ -145,10 +145,10 @@ Controls **how often** dialectic and context calls happen.
| Key | Default | Description |
|-----|---------|-------------|
| `contextCadence` | `1` | Min turns between context API calls |
| `dialecticCadence` | `3` | Min turns between dialectic API calls |
| `dialecticCadence` | `1` (wizard: `2`) | Min turns between dialectic API calls. Unset → every turn; wizard pre-fills `2` |
| `injectionFrequency` | `every-turn` | `every-turn` or `first-turn` for base context injection |
Higher cadence values reduce API calls and cost. `dialecticCadence: 3` (default) means the dialectic engine fires at most every 3rd turn.
Higher cadence values fire the dialectic LLM less often. `dialecticCadence: 2` means the engine fires every other turn. Setting it to `1` fires every turn.
### Depth (how many)
@ -180,6 +180,8 @@ If `dialecticDepthLevels` is omitted, rounds use **proportional levels** derived
This keeps earlier passes cheap while using full depth on the final synthesis.
**Depth at session start.** The session-start prewarm runs the full configured `dialecticDepth` in the background before turn 1. A single-pass prewarm on a cold peer often returns thin output — multi-pass depth runs the audit/reconcile cycle before the user ever speaks. Turn 1 consumes the prewarm result directly; if prewarm hasn't landed in time, turn 1 falls back to a synchronous call with a bounded timeout.
### Level (how hard)
Controls the **intensity** of each dialectic reasoning round.
@ -368,7 +370,7 @@ Config file: `$HERMES_HOME/honcho.json` (profile-local) or `~/.honcho/config.jso
| `contextTokens` | uncapped | Max tokens for the combined base context injection (summary + representation + card). Opt-in cap — omit to leave uncapped, set to an integer to bound injection size. |
| `injectionFrequency` | `every-turn` | `every-turn` or `first-turn` |
| `contextCadence` | `1` | Min turns between context API calls |
| `dialecticCadence` | `3` | Min turns between dialectic LLM calls |
| `dialecticCadence` | `1` (wizard: `2`) | Min turns between dialectic LLM calls |
The `contextTokens` budget is enforced at injection time. If the session summary + representation + card exceed the budget, Honcho trims the summary first, then the representation, preserving the card. This prevents context blowup in long sessions.