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Stability & Quality Status (2026-03-27)

This page documents the current, test-backed stability state of AIRecon.

Executive Summary

AIRecon is not yet in fully stable state for all components.

  • Core proxy/agent logic is largely functional and many tests pass.
  • Full quality gate is still blocked by type-check errors and hanging test suites.
  • "All features 100% working" cannot be claimed yet.

Validation Snapshot

Commands used during this review:

pyright airecon tests --outputjson
pytest --collect-only -q
timeout 180 pytest -q tests/tui
timeout 240 pytest -q tests/proxy
timeout 60 pytest -q tests/proxy/test_server.py
timeout 30 pytest -vv tests/tui/test_widgets.py -s
timeout 120 pytest -q tests/tui/test_app.py
timeout 120 pytest -q tests/tui/test_path_completer.py
timeout 180 pytest -q tests/benchmark

Observed results:

  • pyright: 12 errors (browser, fuzzer, startup, chat widgets).
  • pytest --collect-only: 1376 tests collected.
  • tests/benchmark: 17 passed.
  • tests/tui: timeout (hang).
  • tests/proxy: timeout (hang near completion).
  • Per-file scan in tests/proxy: timeout concentrated in tests/proxy/test_server.py.

Current Blockers

  1. Type-check regressions (pyright not clean):
  2. airecon/proxy/browser.py optional-member errors.
  3. airecon/proxy/fuzzer.py optional-member errors.
  4. airecon/tui/startup.py unused coroutine warning/error path.

  5. airecon/tui/widgets/chat.py optional-member errors.

  6. Hanging tests prevent full CI confidence:

  7. tests/proxy/test_server.py hangs from first status test in current environment.

  8. tests/tui/test_app.py and tests/tui/test_widgets.py time out.

  9. End-to-end runtime coverage is still limited:

  10. No complete local proof yet for all real integrations together (Ollama + Docker + Browser + TUI) in one automated run.

Is Ollama Performance Degraded?

Short answer: it depends on model size and context configuration, not only AIRecon code.

  • Larger models generally provide more reliable planning and tool-use than smaller ones.
  • As model size shrinks, expect weaker planning, more hallucinations, and less reliable tool calls.
  • Context settings still matter: very small ollama_num_ctx values or aggressive truncation can reduce output quality even on larger models.

Stability Exit Criteria

AIRecon can be labeled "stable" after all are true:

  1. pyright airecon tests reports 0 errors.
  2. Full pytest suite finishes without hangs/timeouts.
  3. One automated smoke run validates startup + chat + tool call + report flow against real local dependencies.