Agent skill

train-convo-steering

Voice-first runtime steering + nightly deep analysis to learn per-user conversation priors.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/train-convo-steering

SKILL.md

train-convo-steering (Skill v2)

Voice-first runtime steering + nightly deep analysis to learn per-user conversation steering priors.

This skill is designed for:

  • Live voice: per-turn inference must be fast and bounded (preset selection, not multi-candidate judging).
  • Nightly deep learning: optional DeepSeek V3 (TEE) judge calls to improve labels and update per-user priors.

Concepts

Collaboration State

A compact state bucket per turn (tempo, trust, alignment, affect, control) mapped to {low, mid, high}.

Steering Presets

Configuration of response knobs (length, questions, initiative, certainty, grounding) and voice prosody.

  • fast_proceed
  • clarify_once
  • trust_repair
  • deep_dive
  • exec_summary_plus_steps
  • socratic

Priors

Per-user policy map state key -> best preset learned from reinforcement signals (user feedback, latency, DeepSeek judge).

Commands

Runtime (voice-first)

bash
./run.sh runtime-step \\
  --user-id <USER_ID> \\
  --session-id <SESSION_ID> \\
  --channel <text|voice> \\
  --user-text "..."

Emits JSON with the selected preset and decision details.

Nightly

bash
./run.sh nightly \\
  --logs ./_out/live_logs.jsonl \\
  --out ./_out

Processes logs, runs DeepSeek judge (if configured), and updates priors.

Memory Integration (memory_integration.py)

Cross-session memory persistence via common.memory_client with taxonomy bridge tagging. Priors MUST persist to memory or they are useless across sessions.

Pre-hook: recall_user_priors(user_id, k=10)

Recalls per-user conversation priors from memory for cross-session persistence of learned preferences.

Post-hook: learn_conversation_prior(user_id, prior_type, value, confidence, context)

Learns steering decisions with confidence >= 0.6 during runtime-step.

Post-hook: learn_nightly_summary(user_id, global_best_preset, training_rows, ...)

Learns nightly training results including state policies with confidence >= 0.5.

Bridge Keywords

Bridge Keywords
Precision preference, explicit, specific, configured
Resilience consistent, stable, reliable, proven
Fragility conflicting, unclear, ambiguous, volatile
Loyalty trust, rapport, relationship, familiar
Stealth implicit, inferred, unspoken, behavioral

Tags: ["convo_steering", user_id] + bridges

Configuration

Set environment variables in .env (or project root):

  • DEEPSEEK_API_BASE: Chutes API or gateway URL.
  • DEEPSEEK_API_KEY: API Key.
  • DEEPSEEK_MODEL: Model name (default deepseek-v3).
  • DEEPSEEK_JUDGE_ENABLED: Set to 1 or true to enable.

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