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conversation-lab

Self-improving conversation convergence loop for SPARTA stress tests. Diagnoses unsatisfied sessions, re-runs until personas say satisfactory, outputs structured JSON for /assess consumption. Use when conversation quality is low, sessions are partial, or you need to converge conversations.

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grahama1970/agent-stack-public
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24 de setembro de 2026 às 15:51
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SKILL.md
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name
conversation-lab
description
Self-improving conversation convergence loop for SPARTA stress tests. Diagnoses unsatisfied sessions, re-runs until personas say satisfactory, outputs structured JSON for /assess consumption. Use when conversation quality is low, sessions are partial, or you need to converge conversations.
triggers
["conversation lab","converge conversations","fix unsatisfied sessions","conversation convergence","diagnose conversations","rerun sessions"]
metadata
{"short-description":"Conversation convergence engine","version":"1.0.0"}
provides
["conversation-convergence","session-diagnostics","turn-optimization"]
composes
["sparta-stress-test","review-conversation","episodic-archiver","task-monitor","memory","agentic-evals"]
taxonomy
["validation","iteration","convergence"]
disciplines
["persona-simulation","evaluation-quality"]
> STOP. READ THIS ENTIRE SKILL.MD BEFORE CALLING ANY ENDPOINT. # Conversation Lab Self-improving convergence loop for SPARTA stress test conversations. Follows the Shadow-Lego pattern: run -> assess -> diagnose -> fix -> re-run. ## Commands | Command | Description | |---------|-------------| | `diagnose [file]` | Structured JSON diagnosis for `/assess` (use `--format md` for Rich tables) | | `report [file]` | Full markdown report with conversation transcripts (like `/tmp/conversation_flows_*.md`) | | `data [file]` | Export JSON chart data for `/create-figure` (radar, heatmap, grade distribution) | | `converge [file]` | Re-run unsatisfied sessions until personas are happy or ceiling hit | | `optimize` | Analyze session data + episodic archives to recommend optimal turn counts | | `status` | Show convergence state (running/complete/stalled) | ## Usage ```bash # Diagnose existing sessions (JSON output) ./run.sh diagnose /path/to/sessions_*.jsonl # Run convergence on unsatisfied sessions ./run.sh converge /path/to/sessions_*.jsonl --max-cycles 3 # Dry run (no LLM calls) ./run.sh converge /path/to/sessions_*.jsonl --dry-run # Check turn optimization from episodic data ./run.sh optimize # Human-readable markdown report (full transcripts) ./run.sh report /path/to/sessions_*.jsonl -o /tmp/conversation_flows.md # Export chart data for /create-figure ./run.sh data /path/to/sessions_*.jsonl -o /tmp/charts/ # Then: cd .pi/skills/create-figure && ./run.sh radar --input /tmp/charts/radar.json ``` ## Task-Monitor Integration ```bash # Progress is reported automatically during converge cat conversation_lab_task_state.json | jq ``` ## NDJSON Streaming ```bash ./run.sh converge sessions.jsonl --json-stream | tee converge_results.jsonl ``` ## Convergence Logic 1. **DIAGNOSE** — Read sessions, classify failures (zero QRA, over-clarification, regression, wrong answer, coverage gap) 2. **FILTER** — Select rerun candidates (unsatisfied + rerun_eligible) 3. **RE-RUN** — Call sparta-stress-test with same seeds, higher CONVO_MAX_ROUNDS 4. **COMPARE** — Grade delta between original and new session 5. **ARCHIVE** — Feed improvements to /episodic-archiver 6. **DECIDE** — Converging? Continue. Plateau? Stop. Regressing? Rollback. ### Stopping Conditions - `satisfied_rate >= 0.80` — 80% persona satisfaction - `max_cycles` exhausted (default 5) - Plateau: 2 consecutive cycles with < 5% improvement - Budget: total LLM calls exceed threshold
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