Agent skill
train-convo-steering
Voice-first runtime steering + nightly deep analysis to learn per-user conversation priors.
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_proceedclarify_oncetrust_repairdeep_diveexec_summary_plus_stepssocratic
Priors
Per-user policy map state key -> best preset learned from reinforcement signals (user feedback, latency, DeepSeek judge).
Commands
Runtime (voice-first)
./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
./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 (defaultdeepseek-v3).DEEPSEEK_JUDGE_ENABLED: Set to1ortrueto enable.
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