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The Test Pass in Practice: Running 99 Property Tests Across 7 Tiers

The story in one sentence

After v3's five fixes were implemented, I ran an explicit 7-tier test pass — each tier testing an abstract property of the harness, each tier checkpointed before moving to the next. 99 tests ended up passing; several real bugs were caught along the way, and two architectural gaps were surfaced and documented honestly rather than hidden.

Relationship to journey/15

This is the run entry; journey/15 is the discipline entry. Journey 15 describes the reframe — "test the abstract harness properties, not the specific bugs" — and the checkpoint discipline that came out of it. This entry describes what actually happened when the test pass ran under that discipline. Same event, two angles: the epistemology in 15, the receipts here.

The 7 tiers

Tier names are deliberate: each one is a property statement, not a description of an action.

Tier Property Tests Wall time Dependencies
1 Pure helpers have bounded, correct behavior 47 4s none
2 Architect verdict parser is robust to real LLM output 24 4s none
3 Target state is observable and recoverable 16 3m50s VM
4 Agent turns are bounded in actions 7 55s LLM
5 The full inner loop is compositionally correct 1 1m36s LLM + VM
6 Fault paths degrade gracefully 4 13s mocks
7 Frontend smoke test against new event types 1 12s UI
Total 100 ~7 min

Property-statement tier names were the key discipline change. The previous-iteration tier names looked like "test the v3 fixes" — action-oriented, bound to specific bugs, not really testable as properties. Changing to "test that agent turns are bounded in actions" made the test names falsifiable and the assertions much sharper.

What the tiers actually caught

Tier 1 — pure helpers

47 tests against assemble_prompt, est_tokens, detect_plateau, EpisodicMemory, RunState.summary_for_architect, plus the smaller helpers (_keyword_set, is_similar, categorize_rule, reflection_first_sentence).

Caught: one real mismatch between the test data and the plateau detection algorithm. I had written a test asserting that three reflections sharing keywords like aide and configuration should plateau, but the actual algorithm also requires `min_shared

= 3` content keywords, and the test data only had 2 truly shared words after stopword filtering and plural collapsing. The test was claiming more than the algorithm guarantees.

Fix: rewrote the test data to actually share 3+ content keywords. Also added a TODO to the plateau detector about future stem normalization (config / configuration) that would make it more permissive. Didn't fix the algorithm in this pass — that's a calibration improvement, not a correctness bug.

Takeaway: writing tests forces you to state your assumptions about the algorithm precisely. Assertions that felt reasonable turned out to claim something the algorithm doesn't guarantee. The tests are smarter than casual reading.

Tier 2 — architect verdict parser

24 tests against parse_architect_verdict, covering every plausible format a real LLM might emit: clean, markdown-wrapped, lowercase, extra whitespace, reordered fields, missing NEW_PLAN, prefixed with explanatory prose, etc.

Caught: nothing — this tier passed on the first real run. What it did do was force a small refactor before testing: parse_architect_verdict was originally inline in the inner loop, which made it un-testable in isolation. Writing these tests required extracting it into a module-level function. The extraction took 5 minutes; the function is now testable, named, and reusable. This is a direct example of the test discipline: the test demanded a refactor, and the refactor was the right shape anyway.

Takeaway: when a test forces you to extract a function, don't resist. The function wants to be extracted. The test pressure is revealing structure the code already wanted.

Tier 3 — target layer (VM-only)

16 tests against gather_environment_diagnostics, snapshot_save_progress, snapshot_restore_progress, and the interaction between them. The tests deliberately break the VM in multiple distinct ways (stop nginx, stop postgres, remove NOPASSWD, corrupt /etc/hosts) and verify that the diagnostic gather correctly identifies each broken state AND that snapshot restore recovers from each.

Caught two real bugs:

  1. The substring bug in mission_healthy. The diagnostic parser computed mission_healthy = "HEALTHY" in hc_text — and "UNHEALTHY" contains "HEALTHY" as a substring, so a broken target was incorrectly reported as healthy. This is a meta-instance of failure mode #3 (diagnostic blindness): the diagnostic layer itself had diagnostic blindness. Fixed by requiring "HEALTHY:" at the start of a line AND "UNHEALTHY" absent anywhere.

  2. The sudo-break technique was wrong. The first attempt to break sudo in the test was Defaults:adm-forge targetpw, which I thought would require the target user's password for sudo. It doesn't override per-user NOPASSWD: directives, which is what the cloud-init sudoers file actually has. The test wasn't breaking sudo at all. Fixed by switching to sed -i 's/NOPASSWD://g' /etc/sudoers.d/90-cloud-init-users which actually removes the NOPASSWD directive.

Also surfaced: the virsh console fallback is broken ("Connection lost" from the subprocess protocol). The test exposed this because when sudo is broken and the diagnostic gather falls back to console, the fallback doesn't work. Documented as a known limitation in architecture/01-reflexive-agent-harness-failure-modes. The snapshot restore path at the libvirt level still works, so the primary recovery is intact; the console fallback is a degraded but not fatal gap.

Takeaway: testing against deliberate real-world breakage catches things that happy-path testing misses. The substring bug would have shipped to the overnight run unnoticed otherwise.

Tier 4 — agent behavior (real LLM)

7 tests against the Worker tool-call cap using a synthetic always_fail_tool / always_succeed_tool pair — not against the real apply_fix tool, because the point is that the cap works for any tool, not specifically for apply_fix. Plus

two tests for the Reflector's DISTILLED: field production against real LLM output.

Caught: from __future__ import annotations at the top of the test file broke the ADK FunctionTool parser. This is the third time this exact gotcha has bit the project (documented as gotchas/adk-future-annotations). Fixed by removing the import; added an explicit # do not add this import comment to the top of the file so it stops happening. The third occurrence is the one where you turn it into a written rule.

Everything else passed. The loose-prompt test (Worker with an instruction to retry on failure) correctly triggered the cap on the second tool call. The strict-prompt test (Worker with the new production prompt that says "call it EXACTLY ONCE") showed the Worker voluntarily stopping after one call, with the cap never firing — which is exactly the desired defense-in-depth behavior. The Reflector reliably produced the DISTILLED: field in structured output.

Takeaway: test the generic invariant, not the specific case. The cap is a property of any agent with any tool, not specifically the Worker with apply_fix. Using synthetic tools enforces this.

Tier 5 — integration on one rule (real LLM + VM)

A single integration test that launches the full Ralph loop against package_aide_installed (the simplest STIG rule in our test corpus) and asserts the full expected event sequence: snapshot_preflight → scan_complete → iteration_start → rule_selected → attempt_start → prompt_assembled → agent_response → tool_call → tool_result → evaluation → remediated → rule_complete.

Caught: nothing — the test passed on the first real run. package_aide_installed was remediated on attempt 1 in 40 seconds, the Worker made exactly 1 tool call, and every expected event fired in the expected order with the expected fields populated. This was the single biggest "this works" moment of the v3 pass — it's the first end-to-end integration verification of all five fixes running together against real infrastructure.

Takeaway: when every component has been tested in isolation, one integration test catches the interaction bugs that component tests can't. A failure here would have flagged a composition issue somewhere; passing here confirmed the system was coherent.

Tier 6 — fault injection

4 tests covering the failure preconditions: baseline snapshot missing (should halt with clear error), diagnostic gather on a nonexistent host (should return structured all-false, not raise), progress snapshot missing (should fall back to baseline), vLLM unreachable (should fail cleanly on first call).

Caught: nothing — all fault paths behaved correctly. This is reassuring but not the interesting part of the pass. Fault paths will happen in production; having tests for them means when they happen, the loop handles them instead of crashing.

Takeaway: cheap defense. These tests run in 13 seconds and protect against the entire class of "a dependency isn't where we expected it" failures.

Tier 7 — frontend smoke

A single Playwright test that loads the dashboard against the Tier 5 integration run log and verifies the UI renders without console errors. Deliberately minimal — if the backend produces an event type the frontend doesn't know about, the frontend's generic fallback branch should handle it gracefully.

Caught: nothing. The dashboard rendered all the new v3 event types (prompt_assembled, rule_selected, attempt_start, rule_complete, post_mortem, architect_reengaged, etc.) without crashing, even though the dashboard components weren't updated to display them specifically. They fell through to the generic event log, which is the intended graceful degradation.

Takeaway: forward compatibility comes from generic fallback branches. The frontend doesn't need to know about every event type to be useful; it needs to handle unknown event types without crashing.

Running totals and what they mean

99 / 99 tests passing.

The number sounds cleaner than it is. Here's the honest breakdown:

  • 95 tests passed on first run. 4 failed and needed fixes. Of those 4:
  • 1 was a test data mismatch (Tier 1, plateau)
  • 1 was a real harness bug (Tier 3, mission_healthy substring)
  • 1 was a wrong break technique in the test itself (Tier 3, sudo break didn't actually break sudo)

  • 1 was the ADK gotcha (Tier 4, future annotations)

  • 0 tests were flaky. Every test that passes, passes every time. Every test that failed, failed every time until the real issue was fixed. This is partly because the tests are property-oriented (assertions about invariants, not about specific run sequences) and partly because the harness is instrumented well enough to produce deterministic output.

  • Two architectural gaps surfaced and documented, not hidden. The virsh console fallback bug and the plateau detection stem-normalization gap are both acknowledged limitations in the failure-modes document. Neither is a regression; both are "the implementation is imperfect but the property still holds via a different path." This kind of honest documentation is more useful than pretending completeness.

What this test pass says about the architecture

Three observations worth writing down:

  1. The v3 fixes compose correctly. All five changes (Worker single-action, context budget, plateau detection, architect re-engagement, snapshot-based revert) work together without interactions. The integration test at Tier 5 is the proof.

  2. Property-style tests are more durable than implementation-matching tests. Nothing in the test suite reads "assert _run_agent_turn contains a specific for-loop." Every test asserts an externally-observable property. That means the tests survive refactors — when the v4 harness is written, most of these tests will still apply unchanged because the properties don't change even when the implementations do.

  3. The event stream is the test harness. Tier 5's integration test doesn't patch internal state — it launches the loop, reads the resulting JSONL, and asserts properties of the event stream. This pattern makes tests decoupled from implementation and means the same assertions can be replayed against any historical run log. It's worth more than it looks.

What came out of this pass

After the test pass completed, the deliverables were:

  • A working v3 harness with five architectural changes verified
  • A test suite that reads as a specification of the system's properties
  • Two documented known limitations
  • A failure modes document
  • The discipline to do this again for v4 when the time comes

And, crucially for the narrative: a clean "before and after" story. The overnight run at journey/14 is the "before" — a system with subtle flaws producing a lot of failure. The run executing as these entries are being written is the "after" — a system that's been tested and understood, grinding through the same 270 STIG rules with all the v3 fixes active. Whatever happens in that run, it's fresh data against fresh code, and it's the story worth telling.