LLM finding schemas emit JSON-schema minimum/maximum, which some structured-output endpoints reject #132

Summary

The structured-output response models for LLM analysis, LLMFinding (src/skillspector/llm_analyzer_base.py) and MetaAnalyzerFinding (src/skillspector/nodes/meta_analyzer.py), express their numeric ranges with Pydantic ge/le (start_line >= 1, confidence in [0.0, 1.0]). Pydantic emits those as JSON-schema minimum / maximum. Some OpenAI-compatible structured-output and tool-calling endpoints validate the response schema and reject those keywords, so the LLM call fails before any finding is returned.

Impact

On an affected endpoint, every LLM-backed analyzer (semantic discovery and the meta-analyzer filter/enrich pass) fails the structured-output call, so --llm runs produce no LLM findings even though static analysis still works.

Proposed fix

Drop the ge/le Field bounds, convey the ranges in the field descriptions, and enforce them with runtime field_validators that clamp into range. The emitted schema then carries no minimum / maximum, while the in-code [0, 1] / >= 1 guarantee is unchanged.

Raised while splitting the bounded-reads PR (#19), where @rng1995 asked for this to land as its own change with rationale.