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Market listener text.detect_problem_signal classifier
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Basé sur la classification professionnelle SOC
Use to reconstruct PonyBunny failure paths from logs, traces, state, and runtime evidence in order to identify the first bad transition.
Use when writing ADRs, migration notes, harness principles, verification records, or other technical documentation for PonyBunny.
Use to generate high-signal evaluation cases for PonyBunny changes, including success paths, failure modes, edge cases, and regression-sensitive behaviours.
Use when defining or reviewing runtime events, lifecycle payloads, and event-order expectations for PonyBunny.
Use when designing or reviewing PonyBunny as a harness-first system, especially around boundaries, evaluation flow, observability, and migration structure.
Use when mapping PonyBunny's current state against harness-first best-practice gaps and turning those gaps into actionable engineering inputs.
| name | text-detect-problem-signal |
| description | Market listener text.detect_problem_signal classifier |
| version | 1.0.0 |
| author | PonyBunny |
| tags | ["market-listener","classification","problem-detection"] |
| phases | ["execution"] |
| user-invocable | false |
| disable-model-invocation | false |
Classify whether a piece of text contains a user-expressed problem, pain, or need.
detect_request:
raw_text: string
platform: string
detect_result:
has_problem_signal: boolean
signal_markers: string[]
label: enum [problem, how_to, bug, request, complaint, discussion, showcase, other]
confidence: number