agi-app-tescia-diagnostic 2026.5.22

AGILAB TeSciA-style diagnostic workflow with evidence scoring and regression-plan artifacts

agi-app-tescia-diagnostic

agi-app-tescia-diagnostic packages the tescia_diagnostic_project AGILAB app. It is a diagnostic-method example that turns weak assumptions, evidence, candidate fixes, and regression plans into structured artifacts.

Purpose

Use this package to test a TeSciA-style engineering diagnostic workflow. The default path scores bundled cases deterministically; optional local AI engines can draft new cases, but validated scoring remains explicit and reproducible.

Installed Project

The distribution name is agi-app-tescia-diagnostic; the AGILAB project name is tescia_diagnostic_project. The package exposes both tescia_diagnostic and tescia_diagnostic_project through the agilab.apps entry point group, so AgiEnv(app="tescia_diagnostic_project") resolves the project without a monorepo checkout.

Install

pip install agi-app-tescia-diagnostic

The agi-apps umbrella pulls this package on Python 3.13+ because the TeSciA diagnostic app uses the same Python floor as its packaged worker environment. Install it directly when validating the diagnostic app package from an index or a locally built wheel.

Run In AGILAB

Select tescia_diagnostic_project, open ORCHESTRATE, then run INSTALL and EXECUTE with bundled cases. Inspect the exported reports under ANALYSIS or the project output directory.

Expected Inputs

The default input is a bundled JSON case file. Optional local-AI generation requires a configured local endpoint and fails closed if the generated JSON does not match the expected schema.

Expected Outputs

The app writes diagnostic reports, summary CSV files, reducer summaries, and a student_score field that records whether the diagnosis, better fix, and regression plan are supported by evidence.

Change One Thing

Add one diagnostic case with a deliberately weak proposed fix and two candidate regression tests. The app should keep the stronger fix only when the evidence and tests support it.

Scope

This is a repeatable diagnostic example. It does not execute remediation commands, replace incident management, or silently trust model-generated content.