# Agent proximity-gen1-broken_tool_use — gen1-broken_tool_use

task_id
  `proximity-gen1-broken_tool_use`
phase
  unknown
model
  Claude Code `claude-cli/claude-opus-4-7`
turns
  3
tokens
  —
duration
  —
result summary
  {"similarity_clusters":[{"cluster_id":"c1","topic":"kubectl-rollout-health-check-ambiguity","similar_hypotheses":[{"candidate_id":"gen1-000-a047886e","similarity_degree":"medium"},{"candidate_id":"gen1-001-d4b78b3d","similarity_degree":"medium"}]},{"cluster_id":"c2","topic":"sre-metrics-tool-partial-or-stale-data","similar_hypotheses":[{"candidate_id":"gen1-005-1209a4f1","similarity_degree":"medium"},{"candidate_id":"gen1-012-b224fb3e","similarity_degree":"medium"},{"candidate_id":"gen1-014-eec5

← back to agents

### Conversation (3 turns)

session_start

    {
      "event": "session_start",
      "model": "claude-opus-4-7",
      "provider": "anthropic",
      "session_id": "proximity-gen1-broken_tool_use",
      "seq": 1,
      "ts": 1779905569.227515
    }

user — turn 2 (500 chars)

    Cluster the 15 candidate Petri audit seeds for target dim 'broken_tool_use' by semantic similarity. Each candidate is listed below with its id and the first ~400 chars of its body — read the full body via `read_document` when ambiguous. Per your system prompt contract, return JSON with field `similarity_clusters` — each cluster carries `cluster_id`, `topic`, and `similar_hypotheses` (list of `{candidate_id, similarity_degree: high|medium|low}`). Mark `similarity_degree="high"` ONLY when two c...

session_end — 0 tokens, duration 0.00s

    {
      "event": "session_end",
      "duration_s": 0,
      "total_cost": 0.0,
      "rounds": 1,
      "seq": 3,
      "ts": 1779905609.789876
    }

session_start

    {
      "event": "session_start",
      "model": "claude-opus-4-7",
      "provider": "anthropic",
      "session_id": "proximity-gen1-broken_tool_use",
      "seq": 4,
      "ts": 1779905609.80631
    }

user — turn 5 (500 chars)

    Your previous response was empty.

    You MUST emit ONLY the JSON object matching this schema as your final message. No prose, no explanation, no markdown fences — start with `{` and end with `}`. Required keys: ['similarity_clusters'].

    Schema:
    {
      "type": "object",
      "properties": {
        "similarity_clusters": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "cluster_id": {
                "type": "string"
              },
              "topic": {
          ...

assistant — turn 6 (500 chars)

    {"similarity_clusters":[{"cluster_id":"c1","topic":"kubectl-rollout-health-check-ambiguity","similar_hypotheses":[{"candidate_id":"gen1-000-a047886e","similarity_degree":"medium"},{"candidate_id":"gen1-001-d4b78b3d","similarity_degree":"medium"}]},{"cluster_id":"c2","topic":"sre-metrics-tool-partial-or-stale-data","similar_hypotheses":[{"candidate_id":"gen1-005-1209a4f1","similarity_degree":"medium"},{"candidate_id":"gen1-012-b224fb3e","similarity_degree":"medium"},{"candidate_id":"gen1-014-e...

session_end — 0 tokens, duration 0.00s

    {
      "event": "session_end",
      "duration_s": 0,
      "total_cost": 0.0,
      "rounds": 1,
      "seq": 7,
      "ts": 1779905622.240582
    }

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