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Real-world usage surfaces CLI/codegen defects that pass validate_schema but fail at runtime — e.g. #59 (uuid PK generated with no generation strategy → every insert fails). Catching these today requires a human to notice the runtime failure, diagnose it, build a minimal repro, and file manually. That loop is slow, and most users won't do it — so defects go unreported and unfixed.
Request
An opt-in capability (a CLI "skill", also exposed as an MCP tool) that detects when the CLI produces inaccurate or poor output during normal commands and can automatically open a well-formed GitHub issue against apsoai/cli, grounded in the real usage that triggered it — with user consent.
validate_schema passes but apso dev / runtime errors (validation ↔ runtime divergence).
Codegen emitting unused imports, dead decorators, or asymmetric branches (e.g. serial generates a PK strategy but uuid doesn't).
Migration diffs that fail against the PGlite sandbox.
Schema features silently ignored (e.g. nullable dropped on enum fields).
Repeated runtime errors correlated with a specific generated artifact.
Behavior / guardrails
Opt-in (--report-issues flag or config) — schemas/data may be sensitive.
Sanitize/redact schema + data; include only a minimal repro, versions, and the offending command/artifact.
Dedupe against existing issues (search first; comment rather than duplicate).
Explicit confirmation before opening — especially via the MCP tool.
Auto-attach environment (apso --version, OS, node), the relevant .apsorc excerpt, and the generated snippet.
Integration
A CLI command (e.g. apso doctor --report) and an MCP tool (report_issue / diagnose) so AI agents driving apso can auto-file with the user's OK.
Value
Closes the loop between real usage and CLI quality. Defects like #59 would be detected and filed automatically from actual usage instead of relying on a user to notice, diagnose, and hand-write the report.
Motivation
Real-world usage surfaces CLI/codegen defects that pass
validate_schemabut fail at runtime — e.g. #59 (uuid PK generated with no generation strategy → every insert fails). Catching these today requires a human to notice the runtime failure, diagnose it, build a minimal repro, and file manually. That loop is slow, and most users won't do it — so defects go unreported and unfixed.Request
An opt-in capability (a CLI "skill", also exposed as an MCP tool) that detects when the CLI produces inaccurate or poor output during normal commands and can automatically open a well-formed GitHub issue against
apsoai/cli, grounded in the real usage that triggered it — with user consent.Detectable-signal examples
validate_schemapasses butapso dev/ runtime errors (validation ↔ runtime divergence).serialgenerates a PK strategy butuuiddoesn't).nullabledropped onenumfields).Behavior / guardrails
--report-issuesflag or config) — schemas/data may be sensitive.apso --version, OS, node), the relevant.apsorcexcerpt, and the generated snippet.Integration
apso doctor --report) and an MCP tool (report_issue/diagnose) so AI agents driving apso can auto-file with the user's OK.Value
Closes the loop between real usage and CLI quality. Defects like #59 would be detected and filed automatically from actual usage instead of relying on a user to notice, diagnose, and hand-write the report.