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pbakaus_impeccable/tests/skill-behavior
36457e191f Bump skill-behavior test lineup: gemini-3.7-flash (#598)
* Bump skill-behavior google lineup to gemini-3.7-flash

gemini-3.7-flash replaces gemini-3.6-flash in DEFAULT_MODELS. The
README notes that the recorded gemini baseline cells were measured on
3.6-flash (or 3.5-flash where marked) and count as unmeasured on 3.7
per the suite's own cross-version rule, to be re-run on the next Setup
or routing change.

AI-assisted change.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* Potential fix for pull request finding

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-08-15 19:03:18 -07:00
..

Skill-behavior tests

LLM-backed scenarios that verify how the impeccable skill drives context, command-reference, new-work, and native-platform loading. Each scenario runs against one current model from each supported provider (Anthropic, OpenAI, Google, DeepSeek).

These are the tests you re-run when you refactor anything in SKILL.md's ## Setup section. They fail when the agent stops following the loading contract.

Run

bun run test:skill-behavior
IMPECCABLE_SKILL_BEHAVIOR_VERBOSE=1 bun run test:skill-behavior   # dump per-scenario traces
IMPECCABLE_SKILL_BEHAVIOR_MODELS=claude-sonnet-5 bun run test:skill-behavior   # scope to one model
IMPECCABLE_SKILL_BEHAVIOR_EFFORT=xhigh bun run test:skill-behavior             # OpenAI reasoning effort (default: high)

Requires .env at repo root with at least one of ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_CLOUD_API_KEY, DEEPSEEK_API_KEY. Providers without a key are skipped, not failed.

How it works

Each scenario:

  1. prepareWorkspace() mints a temp dir, symlinks the canonical skill into <workspace>/.claude/skills/impeccable, and optionally writes PRODUCT.md / DESIGN.md fixtures.
  2. runTurn() inlines SKILL.md (placeholders neutralized) as the system prompt and runs Vercel AI SDK generateText with four workspace-scoped tools: bash, read, write, list, and a fake provider-neutral ask_user_question backed by a deterministic simulated user.
  3. The tools record every call into a trace that the test asserts on.
  4. For scenario 4, a second runTurn reuses turn 1's responseMessages so the model sees a real multi-turn conversation.

The trace is the source of truth, not the model's free-form reply.

Scenarios

# Setup Assertion
1 empty workspace runs context.mjs; loads reference/init.md before implementation; automation is not an init bypass
2 PRODUCT.md only runs context.mjs 1-3 times; loads reference/new-work.md to resolve visual authority, establish a world when needed, and develop the surface
3 PRODUCT.md + DESIGN.md runs context.mjs 1-3 times; receives the committed design system and loads reference/new-work.md for the task-scoped concept
4 PRODUCT.md + DESIGN.md, context already loaded in turn 1 turn 2 does not re-run context.mjs
5 PRODUCT.md without the legacy ## Register field and no DESIGN.md runs context.mjs; greenfield craft loads reference/new-work.md, not init, to establish the missing world
6 PRODUCT.md + DESIGN.md + a minimal index.html; prompt is /impeccable polish loads reference/polish.md
7 same fixture; prompt is /impeccable audit loads reference/audit.md
8 PRODUCT.md + DESIGN.md + a SvelteKit scaffold (src/app.css, components, +page.svelte); prompt is /impeccable polish src/routes/+page.svelte reads at least one project code file (CSS / component / page) — not just the skill's reference files
9 PRODUCT.md + index.html + a seeded update cache with a newer version (skillVersion copy-mode so context.mjs has a SKILL.md to version-check against); prompt is /impeccable polish index.html context.mjs runs and its output carries the UPDATE_AVAILABLE directive (proven via captured bash output); the agent does not auto-run npx impeccable update (it must ask first)
10 no PRODUCT.md + a minimal index.html; prompt is /impeccable polish index.html runs context.mjs, loads reference/polish.md, and does not divert into reference/init.md
11 empty workspace; prompt is /impeccable shape ... runs context.mjs; resolves reference/init.md before planning the surface
12 empty workspace; prompt is natural-language build intent with no command word runs context.mjs; resolves reference/init.md before implementation
13 empty workspace; prompt is /impeccable teach runs context.mjs and diverts into reference/init.md because teach aliases init
14 PRODUCT.md with ## Platform: ios (native iOS app); prompt is /impeccable craft a tide detail screen context.mjs runs and emits the contents of reference/ios.md directly, placing native conventions in context without a second model-directed read
15 same iOS fixture; prompt is /impeccable audit agent loads reference/audit.native.md (the Commands-table native variant, routed instead of audit.md)

The workflow-contract file adds end-to-end assertions for attended fresh init, an initialized natural build request, replacement-world redesign, scope-preserving bolder refinement, and critique's closing question. It checks question order and context/artifact writes rather than only reference-file loading.

critique closes with the question or an explicit skip line is a regression guard, not a routing check. A critique that prints its report and then stops, asking nothing and printing no Questions skipped: <reason> line, is an incomplete run: the close is half the deliverable, and polish downstream has no priorities to inherit without it. The fixture page is deliberately broken enough to put the report past the three-Priority-Issue threshold, so the run cannot reach the skip branch on merit. The assertion is deliberately loose about how the run closes, because either close is valid; what it forbids is neither.

Workflow-contract baseline (2026-08-13, current lineup)

Measured while checking whether an {{ask_instruction}} rewrite had regressed anything.

The last two columns are no longer in the default lineup. gpt-5.6-luna and deepseek-v4-flash were dropped in 2026-08 for being below the frontier tier: they fail scenarios by stopping mid-run or archiving a report without stating it, which is model-floor behavior rather than a skill-text defect. Their columns stay here because they are the record of what a weaker model does with this text, and that is the useful part. Reproduce with IMPECCABLE_SKILL_BEHAVIOR_MODELS=gpt-5.6-luna,deepseek-v4-flash.

Against the current default lineup, two cells are the known floor: redesign replaces DESIGN is flaky on every model, and critique closes is flaky on gemini-3.6-flash. A regression is a failure beyond those two.

The Google slot in DEFAULT_MODELS moved to gemini-3.7-flash on 2026-08-15. Every Gemini cell in the tables below was measured on 3.6-flash (or 3.5-flash where marked), and per the cross-version rule further down, those results are unmeasured on 3.7, not inherited. Re-run the sweep on the next Setup or routing change and update the tables to the new column.

Read any failure against the clock before calling it behavior. The suite ran at a 300s per-test timeout until 2026-08-13, and for the workflow-contract scenarios that cap was below the runtime of a correct run. initialized natural build on claude-sonnet-5 was measured at 579s when it stopped to put the concept to the user before building, while the runs that skipped that checkpoint and failed the assertion finished in 130-200s. The cap was therefore selecting for the behavior the scenario forbids: thorough runs were killed, hasty ones were graded. The timeout is now 900s (scripts/test-suites.mjs). A duration at or just past the cap is a timeout, not a verdict.

Scenario claude-sonnet-5 gpt-5.6-terra gemini-3.6-flash luna / deepseek (dropped)
attended fresh init pass pass pass not measured
initialized natural build flaky (1 of 4, and see the clock note) pass pass not measured
redesign replaces DESIGN flaky (timeout this run) fail fail (timeout) not measured
bolder refinement pass pass pass (on 3.5) luna pass, deepseek fail
critique closes pass (4 of 4) pass (3 of 3) flaky (1 of 4) luna fail (1 of 6), deepseek flaky

Gemini's bolder refinement and critique closes runs in this sweep died on AI_APICallError / ETIMEDOUT before completing a turn. Network failures are not behavior measurements and are excluded from the counts above.

Scenario baseline (2026-08-13, current lineup)

Measured on the same sweep. scenarios.test.mjs passes 15 of 15 on gpt-5.6-terra and gemini-3.6-flash. Only claude-sonnet-5 fails anything, and that asymmetry is the finding: the two cells below fail on the frontier model while two weaker-on-paper lineups route correctly, so read them as a text problem that one model's priors expose rather than as a model floor.

Scenario claude-sonnet-5 gpt-5.6-terra gemini-3.6-flash
1-7, 10, 12-15 pass pass pass
8 (SvelteKit exploration) flaky pass pass
11 (shape resolves the build gate) flaky pass pass

Scenarios 8 and 11 pass on re-run, so treat a single failure there as flake and confirm with a second run before investigating.

Scenarios 9 and 15 both failed on sonnet when this baseline was first measured, and the two causes are worth keeping because neither was where it looked:

  • 9 was a real defect in the directive. UPDATE_AVAILABLE said to ask the user, then "If they agree, run npx impeccable update", then to continue without waiting. With no wait there is no agreement to read, so the command was the only concrete instruction left standing and sonnet ran it. Fixed by removing the command from the turn entirely rather than by strengthening the warning around it.
  • 15 was a broken fixture. The iOS workspace held PRODUCT.md and nothing else, so audit the app in this workspace named an app that did not exist. Sonnet spent its whole step budget looking for it and read no reference file at all, which the assertion reported as "loaded audit.md instead of the variant". The fixture now ships one SwiftUI screen, the same courtesy MINIMAL_LANDING_HTML already did for the web scenarios. The scenario passes on unmodified main once the fixture is answerable, which is the proof the routing text was never at fault.

The general lesson is worth more than either fix: an assertion reports the property it checks, not the reason it failed. Both of these read as routing defects and neither was one. Pull the trace before writing the diagnosis, and prefer IMPECCABLE_SKILL_BEHAVIOR_VERBOSE=1 over inference from the message.

Gemini cells marked on 3.5 were measured on the superseded gemini-3.5-flash and have not been re-run on 3.6. That distinction is not pedantic. critique closes passed twice on 3.5-flash, then failed three times in a row on 3.6-flash against identical instruction text, and only passed once the report delivery step was made explicit. A version bump inside one family changed the outcome, so treat cross-version carryover as unmeasured rather than inherited.

not measured means exactly that: the cell was never run in isolation on this lineup. Only the scenarios under investigation were scoped per model. The rows are worth keeping anyway, since a scenario absent from the table is easy to mistake for a scenario that passed.

bolder refinement, deepseek-v4-flash. The model runs context.mjs, reads bolder.md, craft-floor.md, and current.html, then ends its turn without editing anything: empty writePaths, no ask_user_question call, well short of the 16-step cap. Confirmed identical on HEAD with bolder.md reverted, so it is not a skill-text problem. Same shape as the gpt-5.4-mini scenario 6/7 failures below: the model consumes the references and then declines to act.

critique closes: the three ways a critique fails to land. The scenario asserts emission order, not just the presence of a question, because the command fails in three distinct ways and only one of them was the reported bug:

  1. No close. Report lands, no question, no skip line. polish downstream inherits nothing.
  2. Question before report. The question is emitted first and the report after it, so the report is withheld until the user answers. Observed directly on gpt-5.6-luna, and the reason the invariant is a position rule ("the question is the LAST thing in the response") rather than a statement about prose order.
  3. Report never spoken. The report is authored straight into the persistence heredoc, archived, and never written to chat. A perfect snapshot and a user who sees nothing.

Mode 3 is the one worth understanding, because it was structural rather than a model quirk. critique.md described the report's format and then went directly to writing a temp file, with no step that said to output the report. Both gemini-3.6-flash and luna responded by bundling heredoc, snapshot write, trend read, and cleanup into a single bash call and stopping. The Deliver the Report section exists to close that gap, and it worked: gemini-3.6-flash failed three consecutive runs before it, and its failures afterward all show the report reaching chat.

Mode 1 is not fixed on gemini-3.6-flash. It passes 1 run in 3 on the final text. Two structural attempts were made and neither settled it: the close was promoted into Hard Invariants with a printable Questions skipped: <reason> string, then made step 6 of the persistence list so it would sit inside the numbered flow rather than after it (the shape that fixed mode 3). Both moved it from consistently failing to intermittently passing, and further prose tuning was not paying, so it stopped. claude-sonnet-5 and gpt-5.6-terra are clean. Treat this cell as the known floor and re-measure rather than tuning blindly: the next useful move is probably a structural one, such as making the close something the run cannot syntactically finish without, not another paragraph.

Read the counts here as what they are: small samples on a nondeterministic system, several of them gathered while the instruction text was still changing between runs. They support "the close works on the current lineup" and not much finer than that. Re-measure rather than assuming when the lineup changes.

redesign replaces DESIGN, flaky. It has failed on two different assertions across runs (designWrite > question and implementation > designWrite), and on one run claude-sonnet-5 exhausted the 300s per-test timeout instead of asserting. The traces never load document.md; the ordering under test comes from new-work.md. Re-run before believing a single red result here. Which model produced which failure was not pinned down, so the row records only that the scenario is unstable.

The bolder claude-sonnet-5 cell is unmeasured for a specific reason: the scoped run that produced this table used a 180s cap, which sonnet exceeded. That is a timeout, not a failure, and it is why the guidance below insists on 300000.

Scoping a run while investigating

Both files honor --test-name-pattern, which is much cheaper than a full sweep when bisecting one scenario:

IMPECCABLE_QUESTION_DISABLED=1 CI=1 IMPECCABLE_SKILL_BEHAVIOR_MODELS=deepseek-v4-flash \
  node --test --test-timeout=300000 --test-force-exit \
  --test-name-pattern="bolder refinement" tests/skill-behavior/workflow-contract.test.mjs

Keep --test-timeout at 300000. A tighter cap turns claude-sonnet-5's slower runs into timeouts that look like failures. Set IMPECCABLE_QUESTION_DISABLED=1 and CI=1 so serve-question.mjs cannot open a browser window on the host. Pipe to a file rather than tail; node prints the failing-test summary at the end, and truncating it costs you the per-model attribution.

Baseline state (2026-05-20, previous cheap tier)

Historical record. The default models are now claude-sonnet-5 and gemini-3.6-flash. The table below was measured on an older cheap tier (claude-haiku-4-5 / gpt-5.4-mini) and is kept as the historical record. Re-measure on the current lineup and update this section; the stronger models are expected to clear the scenario 6/7 routing failures that the old gpt tier showed.

Captured after moving sub-command reference loading from step 4 to step 2 of Setup (so the agent loads reference/<command>.md right after context.mjs, before "doing the work" preempts it), and tightening step 3 to require at least one project code read even when a sub-command reference loads first. Use this table when comparing pre/post refactor: a regression is "more failures than baseline", not "any failures at all".

Scenario claude-haiku-4-5 gpt-5.4-mini gemini-3.1-flash-lite
1 (no context) pass (rare flake — agent stops after context.mjs without loading init.md) pass pass
2 (product only) pass pass pass
3 (product + design) pass pass pass (rare flake — sub-command ref loads but world ref doesn't)
4 (already loaded) pass pass pass
5 (no register field, task-cue cascade) pass pass pass
6 (polish routing) pass fail pass
7 (audit routing) pass fail pass
8 (existing project, explore design system) pass pass pass

21-22 / 24 typical. The stable failures are gpt-5.4-mini scenarios 6 and 7: the model reads index.html (the target file), recognizes "polish" or "audit" as a familiar action, and proceeds with the work without ever loading the sub-command reference. Stronger SKILL.md wording (MUST, "non-optional", reordered earlier) didn't move it; this looks like a model-floor behavior rather than a skill ambiguity. Claude and Gemini honor the load.