test-driver/docs/TestDriverGeneralisationReview.md

# TD-WP-0003 generalisation and settlement — 2026-09-28

The kernel now expresses sharing/revocation, delegated approval and tenant
lifecycle without additional framework concepts. This is evidence of local
expressiveness, not readiness for autonomous verification of a real system.

## New use cases (T02)

The agent wrote [synthetic contracts](../usecases/generalisation-spec.md) before
the implementations. Claims are `agent-from-spec`, not human-authored. The same
agent wrote the synthetic requirements and labs; this does not establish
independence from a real product team or requirements quality.

- `scenarios/delegated_approval.py`: premature execution, submission, delegation,
  rejected self-approval, rejected former-reviewer approval, delegate approval,
  requester execution. Three independently enabled defects must fail.
- `scenarios/tenant_lifecycle.py`: two administrators use the same local id;
  foreign delete attempts fail; deletion and recreation preserve the other
  tenant. Four independently enabled defects must fail.

`tests/test_generalisation.py` verifies baselines, each defect, missing-evidence
INCONCLUSIVE, deterministic replay and verdict reproduction from serialized S3.
Separate observers read state and probe enforcement; drivers only emit S1.
No claims or invariants are learned from the lab's responses.

Ordered `Step`s already express the required Schedule. `Scenario.variant`
identifies each lab fault. A separate scheduler, Lens or Variant object was not
needed. There is no concurrent scheduling or time-window evidence here.

The resistance was in the adapters, not new concepts: `StateObserver`'s standard
snapshot is specific to resource grants, so each domain needs its own collector
implementing `snapshot()` and `name`. Expected refusal must be a completed
protocol response with an independently observed receipt; setting
`Realization.raised` would suppress dependent claims as INCONCLUSIVE. Unexpected
exceptions still abort these fixture drivers; they are not silently swallowed.

## Structural experiment (T03)

[Machine-readable results](../research/evidence/2026-09-28-e001.json) retain each
arm's surface, judgments, metrics and the journey classification/signals.
Reproduce with:

```bash
PYTHONPATH=src:. python3 tools/measure_e001.py /tmp/e001.json
```

| Identifier axis | Discovery | Recorded selectors |
|---|---:|---:|
| Preserved | 17/17 | 17/17 |
| Dropped | 9/10 | 0/10 |

M25–M31 add reordered fields, dialog relocation, anchor affordances, fieldset
grouping, textarea input, an unrelated preceding form, and sidebar relocation.
M32–M38 pair those mechanisms with preserved identifiers. Existing M02/M21/M22
supply rewritten DOM, reworded controls and renamed fields. New labels were fixed
from the synthetic contract before running and are agent-authored, not claimed
as newly human-reviewed ground truth.

The 38-entry catalogue contains 27 mechanical, four semantic and seven defect
mutations. Mechanical acceptance is 26/27. M22 still defeats the heuristic.
False adaptation is 0/7 on the existing defect set; adding mechanical variants
does not enlarge that safety denominator. No claim/invariant index changed.
M25 and M32 are UNCHANGED because the coarse surface fingerprint ignores field
order and test ids; this is not a claim that their HTML is identical.

These are selected mechanisms, not random independent samples. Paired variants
are correlated; 9/10 is not a population reliability estimate. The control is a
stable-test-id replay, not every possible conventional selector strategy. Both
arms remain token-free and test structural HTML only. H-001 stays narrowed to
identifier-loss cases, and F-0004/F-0005/F-0007's external validity limits remain.

## Concept settlement and compatibility (T04/T05)

**Keep claims as Python predicates.** Across all three runnable use cases the
repeated shapes are equality, membership and comparisons between enforcement
and state. The audit-core consumer additionally compares sanitized absence
surfaces, bounded execution, cleanup and receipt binding. A small vocabulary
would either duplicate Python or need frequent escape hatches; serialization
would create a second language and a second statement of intent.

This publishes the interface decision requested by T05: the existing
`Claim(id, text, provenance, predicate, after_step, source_ref=None)` and
`Invariant(id, text, provenance, predicate, source_ref=None)` constructors stay
compatible. Predicates receive independent observation mappings and return
booleans. Required evidence must use explicit lookup, not a pass-producing
fallback. The oracle converts missing keys or predicate exceptions to
INCONCLUSIVE. Predicates must not reach into actors or the live SUT.
Generated regression artifacts continue to import their original scenario
claims; consumers must ship those modules with the artifact. Fully standalone
claim serialization is deliberately rejected. The audit-core consumer needs no
migration; its tests remain in the default suite.

**Remove unused lifecycle concepts now.** Temperature, Energy, Confidence,
Campaign, Metabolism and automated Retirement have informed no decision in
these three use cases. They leave the current model, not another deferred gate.
Trajectory stability continues to drive crystallization. H-005 becomes
`DORMANT-INDEFINITE`; F-0008 is resolved.

This is a research-prototype compatibility change: `testdriver.energy`, public
`EnergyEvent`/`EnergyEventType` exports and the `EvidencePack.energy_events`
field are removed. Consumers must stop importing or requiring them. Historical
JSON may retain that field; the current classifier already ignores it.
Execution identity, timestamps, judgments, S1 realization costs and lineage
remain; none of these imply a computed lifecycle score. There is no dependency
addition. Historical concept proposals carry a supersession notice.

## Authoring measurement (T07 remains waiting)

[Timing receipt](../research/evidence/2026-09-28-authoring.json) preserves the
actual measurements and line counts. The timer was placed inside the shell
write operation, after code composition. The approval interval also included
composition of the next case, and the tenant interval largely measured file
writes and pytest. These intervals are **not valid authoring-cost measurements**
and must not be compared as productivity numbers. Human maintenance effort and
model latency/cost were not captured. The first attempt cannot be reconstructed.

The observable concepts consulted and friction are recorded above. T07 retains
the remaining work: an independent author must implement these contracts afresh
with a timer started before reading/design, stopping after first passing defect
checks, separately recording tooling wait and review. Do not count a rerun or
copy of these implementations as a new authoring sample. No replacement task
or workplan is created.

## Real-system readiness (T08)

**Verdict: not ready for autonomous real-system application.** Local research and
attended review of prepared claims can continue. Completing the review does not
satisfy the workplan's live-model success gate or authorize a production run.

| Required criterion | Current evidence | Assessment |
|---|---|---|
| Independent observation channel can read records and probe enforcement without trusting actors | Three labs; audit-core declares an independent observer but has no runnable driver/collector here | Not met outside synthetic labs; adapter construction, permissions and operating cost remain unmeasured |
| Claims trace to independently approved intent predating the tested behavior | Local provenance guards; audit-core cites approved engagement and workplan, while its precedent receipt is calibration only | Structurally supported, operational chain must be checked for the exact next engagement; a ticket written after code is insufficient without human promotion |
| Legitimate behavioral ambiguity is escalated without rewriting intent | M12/M19 are behaviorally indistinguishable; AMBIGUOUS and BEHAVIOUR_CHANGED require review | Demonstrated in lab, real backlog dispute resolution is still attended; missing evidence stays INCONCLUSIVE |
| False-adaptation consequences are identified for the engagement | Audit-core tenant disclosure, forged foreign append or leftover identity could be concealed by a false pass | Zero tolerance for automatic acceptance of regression; 0/7 synthetic defects is no guarantee against unseen attacks |
| Execution, custody, timing, cleanup and target revision are enforced | Audit-core's PhaseContract is durable intent, explicitly not a runnable Scenario; tests use supplied observations | Not met: no causal/time-window runtime, custody or cluster driver, independent cleanup collector or fresh admitted window here |
| Capability, economics and maintenance costs justify adoption | Token-free structural discovery, deterministic crystallization and invalid first authoring timer | Not met; T01/T06/T07 retain the unanswered measurements |

The audit-core material referenced here is the checked-in
`usecases/audit_core_e2_tenant_boundary.py` contract and its fixture-based tests,
not a fresh inspection of any deployment or a revalidation of the 2026-08-22
engagement. A real run needs the exact engagement's target-owner acceptance,
independent observation/cleanup receipts and appropriate approved access. A
successful historical receipt cannot substitute for those. The existing T01,
T06 and T07 tasks retain the experiment blockers; this review creates no
production implementation commitment or new work record.

## Safety follow-up: aborted runs and incomplete evidence

A post-closeout review reproduced two false-pass paths that the original suite
missed. A forbidden-surface exception after a passing prefix returned PASS even
though later claims had never been judged. Separately, deleting almost every
judgment and all state snapshots still yielded UNCHANGED/safe-to-accept.

The runner now records `scheduled_steps` and `expected_judgments` from the
scenario before executing any action. Only claims attached to scheduled steps
are included; the existing one-step browser scenario remains intentionally
narrow. On a surface violation, every remaining scheduled claim and invariant
gets an explicit INCONCLUSIVE judgment and no fabricated observation. A prior
FAIL still dominates. An abort after the last assertion is also INCONCLUSIVE,
because completing the assertions does not mean the scheduled run completed.

The classifier validates both packs against their input manifests. It requires
exactly one judgment for every expected assertion/step pair and exactly one S1
realization, S2 realization check and nonempty S3 state snapshot for every
scheduled step, with the correct strata. Missing, duplicate or invalid verdict
records, unfinished runs, and missing identity/version fields prevent automatic
acceptance. The candidate must retain the baseline's step and judgment coverage.
Evidence failure returns AMBIGUOUS before any adaptation rule is considered.

This adds two serialized EvidencePack fields. Historical packs without these
manifests remain historical artifacts but classify as AMBIGUOUS; rerun the
scenario to obtain evidence eligible for automatic acceptance. Do not infer a
manifest from surviving observations, since that would preserve the original
hole. These checks establish structural completeness, not authenticity of a
pack or correctness of arbitrary caller-supplied predicates. The existing
actor/observer separation and deterministic oracle remain required.

Regression coverage in `tests/test_evidence_completeness.py` includes aborts at
each step, abort after the final assertion, preservation of an earlier failure,
individual missing strata/records, duplicate records, and identical truncation
of both packs. Complete ordinary runs and intentionally narrow scenarios retain
their existing behavior. The two defects are handled under the existing T08
readiness review; the external T01/T06/T07 blockers remain unchanged.

Validation after the safety fixes: **299 tests passed** (`python3 -m pytest -q`).
The new regression module had 55 failures and five passing controls before the
fix; `git diff --check` passes after it.

## Admission follow-up: crystallization and intent revisions

The next boundary review reproduced three additional holes: repeated aborted
runs qualified as stable; a complete failing run compared with itself was
UNCHANGED/safe-to-accept; and changing a claim's text or predicate while retaining
its ID/provenance was invisible to the classifier. These fixes remain under T08.

Crystallization now uses the classifier's acceptance gate for every run against
the first run. All packs must have complete evidence, passing judgments, verified
postconditions, unchanged intent and successful realizations. Scenario/use-case
identity, scheduled steps and expected judgments must match across the window.
Repeated copies of one run receipt do not satisfy the independent-run count.
Only then does trajectory comparison decide stability. A refused window returns
no trajectories. An unchanged product failure is not a stable success.

The classifier requires a passing baseline. If the baseline contains FAIL or
INCONCLUSIVE, even a repaired candidate requires a new passing reference rather
than automatic acceptance against the failed baseline. Candidate failures against
a passing reference still report BEHAVIOUR_CHANGED. Baseline realization must
also be established before either automatic-acceptance outcome is returned;
missing or non-boolean postconditions cannot be treated as success.

Evidence packs now include `intent_revisions`: SHA-256 revisions recorded before
execution for the use case and each claim/invariant, including claims outside a
partial scenario's schedule. They include narrative or assertion text, source,
provenance, claim scheduling, and predicate implementation. The predicate hash
covers bytecode/constants, defaults, keyword defaults, closure values, referenced
Python helper functions and their referenced global values. It is bound to the
Python implementation/version; checkout filenames and line numbers are excluded.
Only hashes enter evidence, not captured values or code. Changed definitions
produce INTENT_CHANGED, which requests review and does not assert human approval.
An internally complete revised claim schedule is an intent change; missing
baseline coverage under unchanged intent remains incomplete evidence.

No Claim/Invariant constructor change or claim serialization language is added.
`revisions.py` is input-change detection for pure Python predicates. It does not
prove semantic equivalence, sandbox Python, attest a caller-supplied pack or make
mutable runtime behavior safe. Predicate dependencies must stay stable during a
run. Cyclic/opaque callables, module dependencies and dynamic builtin lookups
cannot be fingerprinted reliably and receive a null revision. They may still be
evaluated by the oracle, but their evidence cannot be automatically accepted or
crystallized. Refactor such predicates to consume plain independent snapshots.
Changing Python versions conservatively requires intent review and fresh evidence.

Older packs without usable intent revisions require a rerun, just as packs
without the earlier completeness manifest do. Existing historical experiment
receipts are not retroactively upgraded or rewritten. Tests in
`tests/test_acceptance_boundaries.py` cover the reproduced cases, helper/global
and captured-value changes, invariant/narrative/source/scheduling changes,
cross-process identity, source relocation, redaction of captured values, malformed
postconditions, and the complete-passing control. No live-model, browser-engine
or production readiness blocker is removed by this work.

Validation for this follow-up: initial reproduction had 20 failures and two
passing controls; full suite **327 passed**. The final dynamic-dependency and
strict-postcondition additions passed **32 boundary checks**, including four
new cases. These counts overlap; they are not separate independent samples.