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PaperClipAI/tests/runner-e2e/FIXTURES.md
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DottaandPaperclip 846336e5a0 test: harden agent chat setup, interruptions and restart evals (#13762)
## Thinking Path

> - Paperclip lets people manage agents through ongoing conversations.
> - Chat users can change instructions while a provider is already
working.
> - Existing chat evals wait for each turn to settle before the next
message.
> - They cannot prove delivery during active work or the saved effect of
a correction.
> - Existing fixtures also enable Agent Chat through the API rather than
the settings UI.
> - This PR adds bounded browser workflows and checks their persisted
outcomes.

## Linked Issues or Issue Description

Refs #13741, #13752, #13750.

**What happened?**

The chat suites cover planning, delegation, status, and recovery. They
lack active-turn follow-ups and the experimental settings lifecycle. A
sequential conversation can pass even if messages sent during work are
lost.

**Expected behavior**

A follow-up submitted during a provider turn survives and affects the
final reply. A changed launch day appears in the saved plan. Disabling
Agent Chat rejects new messages while preserving history; re-enabling
resumes the same conversation.

**Steps to reproduce**

Run the explicit `agent-chat-stories` suite. It selects three local
cases for each native Claude and Codex profile. An ordinary provider
command waits for a fixture brief file so the browser can send the
follow-up at an observed active-run boundary.

## What Changed

- Add six opt-in Product E2E cells for settings, active follow-ups, and
plan corrections.
- Drive experimental settings through the UI and verify disabled sends
are rejected by the public API.
- Use a bounded file wait in the actual isolated agent workspace, with
provider-written readiness and an undisclosed brief reference.
- Grade persisted user messages, final replies, native run outcomes, and
exact saved plan fields.
- Accept active-turn steering or one queued successor; reject lost
input, duplicate input, and stale outputs.
- Allow one steered run or two sequential runs throughout the shared
harness, while preserving exact counts for other cases.
- Require a single marker-bearing response attributed to the final
provider run.
- Unload the development browser client before restarting the server,
avoiding reconnect/navigation races without weakening the post-restart
memory check.
- Add browser regressions for restart isolation and asynchronously saved
settings switches.
- Document prepared-agent setup, native onboarding limits, and the
separate API-tool rollout gate.

## Verification

- Eval TypeScript check passed.
- Eval support suite: 436 tests passed in 39 files.
- New oracle calibration: six tests passed, including plausible invalid
outcomes.
- Browser support regressions: seven tests passed; the restart
regression was observed failing before the fix.
- Catalog discovery selects exactly six local native cases and leaves
default paid selection unchanged.
- [Consolidated existing native chat
report](https://d1p6rlowie26tp.cloudfront.net/runner-e2e/campaigns/gha-35643286055-1/):
master `b82661b56`, 33/34 passed, all cleanup passed. The failure was a
browser navigation timeout across restart; the page request returned 200
and the chat rendered.
- [Nine targeted restart/replay
cells](https://d1p6rlowie26tp.cloudfront.net/runner-e2e/campaigns/gha-35645850088-1/)
passed on `1fe2fe275`, including the original failure, across native
Claude/Codex and local/Daytona; all cleanup passed.
- [Initial six-story
campaign](https://github.com/paperclipai/paperclip/actions/runs/35644832817)
retained all six failures: asynchronous switch assertions, unavailable
fixture paths, and rich-text escaping in raw command comparisons. The
corrected fixtures preserve the same behavioral assertions.
- [Six-story campaign
v2](https://d1p6rlowie26tp.cloudfront.net/runner-e2e/campaigns/gha-35646270035-1/)
on `8232773a0`: 4/6 passed (both settings cases and both Claude
interruptions). Codex could not see the host-temp fixture outside its
workspace; this failed before follow-up delivery was exercised.
- [Four affected interruption
cases](https://d1p6rlowie26tp.cloudfront.net/runner-e2e/campaigns/gha-35647760635-1/)
all passed, including cleanup, on definition v3 / `ad6ac0545`. Files
live inside the actual agent workspace and the observed run workspace is
verified. Both providers saved Friday in the real plan with the
undisclosed brief reference; follow-ups persisted while the original run
was active. Together with both unchanged settings cases from v2, all six
new scenario variants have passing live evidence.
- Final head `ad6ac05456646c09d3452e320279457625353948`: 54 successful
checks, two intentional skips, zero pending/failing checks; mergeable
and clean. Fresh Greptile 5/5, zero unresolved findings.
- Full typecheck, tests, build, and browser CI passed remotely. One
earlier head encountered a signoff-policy browser timing failure; the
final head passed that shard.
- Local pnpm wrapper could not fetch its version/signature metadata in
the restricted environment; local eval checks used the installed Node
executables. Repo-wide validation was completed by GitHub Actions.

## Risks

These are eval-only changes. The file wait is a timing fixture in the
isolated agent workspace, not a production runner hook. Native Codex
host-filesystem isolation stays unchanged. It has a two-minute limit and
is released in `finally`. The prepared-agent settings case is not full
native onboarding: the wizard currently offers legacy adapters. The
disabled-entry assertion uses full document navigation, which clears the
prior React Query cache; preserved history is checked through the public
API and re-enabled chat. No production prompt, rollout default, adapter
behavior, or credential policy changes. Active-task reassignment and
worker-crash recovery remain outside these new cases.

## Model Used

OpenAI Codex, GPT-6, with repository tools and code execution. The exact
deployment model ID and context window are not exposed in this task.

## Checklist

- [x] I have included a thinking path that traces from project context
to this change
- [x] I have specified the model used (with version and capability
details)
- [x] I have checked ROADMAP.md and confirmed this PR does not duplicate
planned core work
- [x] I have searched GitHub for duplicate or related PRs and linked
them above
- [x] I have either (a) linked existing issues with `Fixes: #` / `Closes
#` / `Refs #` OR (b) described the issue in-PR following the relevant
issue template
- [x] I have not referenced internal/instance-local Paperclip issues or
links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip`
URLs)
- [x] My branch name describes the change (e.g. `docs/...`, `fix/...`)
and contains no internal Paperclip ticket id or instance-derived details
- [x] I have run tests locally and they pass
- [x] I have added or updated tests where applicable
- [x] I have updated relevant documentation to reflect my changes
- [x] I have considered and documented any risks above
- [x] All Paperclip CI gates are green
- [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups
- [x] I will address all Greptile and reviewer comments before
requesting merge

---------

Co-authored-by: Paperclip <noreply@paperclip.ing>
2026-09-21 16:18:06 -05:00

11 KiB

Runner E2E fixture authoring

The fixture catalog is executable production-contract data. Keep it small, typed, deterministic, and free of raw credentials.

Suites and matrices

A RunnerSuiteFixture declares one durable testing purpose: stable ID, label, description, profiles, environments, cases, expected size, and definition or ranking metadata. Its execution IDs are globally prefixed as <suite>.<profile>.<environment>.<case>. Add a new suite when the testing purpose or desired cross-product differs; do not inflate an existing suite with unrelated dimensions.

The suite definition fingerprint is historical comparison metadata. Any profile, model qualification, environment, task, or ranking-snapshot change must change that fingerprint automatically so the dashboard can annotate the boundary instead of silently joining unlike totals.

Agent profiles

Add RunnerProfileFixture entries in catalog.ts. A profile declares:

  • a stable ID and searchable groups;
  • legacy or native generation;
  • adapter/provider and required credential;
  • a model imported from its adapter constant or qualified runner profile;
  • supported environment IDs;
  • expected runtime metadata; and
  • an agent payload factory.

Do not duplicate model IDs, qualification decisions, CLI versions, or runner artifact rules. Codex profiles import DEFAULT_CODEX_LOCAL_MODEL, OpenCode profiles import QUALIFIED_OPENCODE_MODEL, and ACPX profiles import QUALIFIED_ACPX_PROFILES. Add or qualify models at their owning production source first.

OpenRouter breadth profiles are generated from openrouter-models.json, not written by hand. That reviewed snapshot must contain exactly five unique, available, tool-capable models with rank, canonical ID, display name, supported parameters, source URL, capture time, and verified content hash. Refresh it manually with pnpm test:e2e:runner:models:update; nightly campaigns never change fixture definitions.

Agent adapterConfig.env values must be {type:"secret_ref", secretId, version:"latest"} objects supplied to the factory. A fixture source containing a raw secret-looking value is rejected by catalog validation.

Environments

An EnvironmentFixture declares driver/provider, credential requirements, attempt deadline, lifecycle behavior, expected execution target, and a payload factory validated by the shared environment schema.

The local environment is instance-managed: company creation ensures it exists, and the public API intentionally rejects a second local environment. The setup registry therefore discovers that row through the public environments API. This still provides full isolation because every cell starts a new Paperclip instance and database.

Daytona creates sandbox environments through the public API. The core fixture keeps reuseLease:false and runnerLifecycleMode:"per_turn". The dedicated warm-continuity fixture uses reuseLease:true and runnerLifecycleMode:"warm"; its distinct configurationKey is part of the suite fingerprint even though both fixtures report environmentId:"daytona". Keep short provider cleanup backstops, a Daytona secret reference, and an immutable image digest. Teardown must delete the environment with reusable-lease destruction and must fail the cell if cleanup cannot be confirmed. Keep CPU, memory, and disk explicit: lease metadata and the per-test public-list-price runtime estimate depend on that pinned billable resource shape. Changing it requires updating billing tests and reviewing the versioned Daytona rates in billing.ts.

Usage and billing data

Do not add fixture-authored token or dollar expectations. The live harness reads usage from selected public heartbeat-run records and records coverage per run. Provider-reported dollars remain distinct from runtime estimates. A zero or missing native usage payload is unavailable unless a real token-bearing receipt or provider cost proves otherwise. New execution environments must provide lease/resource metadata for a runtime estimate or explicitly remain unavailable; never infer that missing billing data means free execution.

Future providers (SSH, E2B, Modal, Cloudflare, Kubernetes, Novita, exe.dev) should implement the same setup/probe/cleanup contract before being added to a matrix. Unsupported profile/environment combinations belong in supportedEnvironments, not in ad hoc test conditionals.

Task cases and matchers

A RunnerTaskFixture owns a work mode, a typed flow, expected run count, nonce-based title/prompt/marker factories, per-environment attempt deadlines, deterministic matchers, and expected terminal state. Single-turn prompts should make one bounded request with observable output and no nondeterministic judging. The plan_revision_acceptance flow must also provide revision-request and Plan marker factories. question_resume_completion must define the deterministic browser answer and prove exactly two successful runs with no pending interaction. plan_approval_completion must target the exact two-step canonical Plan revision, capture its pending UI, approve in the browser, and prove exactly two successful runs. warm_three_turn provides exactly two browser follow-up messages, preserves one project/execution-workspace scope, verifies host file contents after every turn, and finishes within three ten-minute turn deadlines. Native turns 1 and 2 include an actionable human review in the completion report's attentionRequests. Paperclip creates the review gate from that report. An explicit question-tool wait yields the turn and suppresses its final prose, so it is not interchangeable with this completion-review fixture. Turn 3 reports Done without another review.

Every selected case runs in its own isolated Paperclip process, and independent cases may run concurrently. Follow-up turns inside one case retain their shared task state. Each case creates and tears down its own company, secrets, environment selection, agent, and browser-created task. The current plan case proves three runs on the same issue: publish a two-step Plan, request a three-step revision through the UI, and accept the exact new revision through the UI before verifying implementation and Done.

The matcher union supports message exact/contains/regex/ordered checks, issue and run state, runtime/environment metadata, files, artifacts, JSON paths, and JSON Schema. The initial cases use normalized message_contains plus state, runtime, and environment assertions; the plan flow additionally verifies canonical document revision IDs, bodies, step counts, interaction targets, and visible previews. Add matcher behavior and credential-free tests together.

Adding a task expands its suite's matrix. Update the suite's intentional size, the complete-catalog size, and credential-free unit tests in the same change. Paid tests never silently skip a missing credential or unsupported artifact.

New Paperclip object fixtures

Register new objects in live-fixtures.ts with explicit dependencies in FixtureRegistry. Setup must use a public API. Teardown runs in reverse order and is invoked after partial setup failures. Direct database writes and private test-only runner endpoints are prohibited.

The expected dependency shape is:

company
└── encrypted secrets
    └── environment
        └── agent
            └── browser-created task

Projects, goals, apps, and configuration fixtures can be inserted into that graph without changing the launcher. Keep returned fixture state to IDs and sanitized metadata; never retain raw secret values.

Required checks

Run before a fixture change is reviewed:

pnpm test:e2e:runner:unit
pnpm test:e2e:runner:typecheck
pnpm test:e2e:runner -- --list

Then run the narrowest paid cell that exercises the fixture. A full matrix is a manual or scheduled campaign, not a PR requirement.

Persistent chat fixtures

chat-cases.ts defines the eight-case agent-chat suite; chat-flow.ts drives the production composer, plan revision/approval controls, questions, reset command, and project cards. Keep its 28 local cells intentional. expectedRunCount counts provider turns, including cancelled and handed-off task runs, but excludes synthetic /new runs. Assertions must inspect all company runs because ordinary issue lists exclude the source conversation. assertChatHandoff rejects missing projects/plans, chat children, wrong assignees, and execution before plan commit.

Retained api-state.json, chat-handoff.json, and plan-revision evidence include persisted comments, session generations, run context and logs, project workspaces, task documents, and ordering. They pass through the normal sanitizer. Screenshots are allowlisted to the exact disposable agent chat. Cleanup cancels all active runs in the isolated company, including handed-off work; usage from failed and cancelled runs must not disappear from campaign totals.

Warm three-turn continuity grades the exact workspace file after each turn, task completion, and sandbox/session identity. It also requires a visible persisted final reply with each turn marker once and in order. It does not grade exact final-reply wording; the hello and continuation fixtures retain those exact-response checks. This separates workspace persistence failures from model response-format variance.

chat-hardening.ts adds the explicit-only agent-chat-hardening journeys. Use the ordinary public APIs to seed source documents and blockers. Keep the answer out of the user's status/review request. Grade the exact source values, latest blocker, preserved task identities, worker-authored output, and real executions. The status request asks for JSON so the grader can distinguish the current blocker from a historical mention and compare active-run count separately from task status. The request must not reveal those expected values. Capture the source after seeding and compare every field in the public issue update contract, plus labels, dependencies, and dedicated-endpoint settings. Derived inbound references may change when the chat legitimately cites a task. The lost-acknowledgement probe may interrupt only the fixture browser's own comment request after the real server has committed it. Retain its request ID and replay that same request through the public API after restarting the server. Never fabricate tool results or repair task state after a failed assertion.

chat-stories.ts seeds an ordinary file wait in the isolated agent's actual home workspace; native Codex intentionally cannot see arbitrary host temp files. The observed run workspace must match the fixture location. This is a deterministic interruption boundary. The real provider command writes the readiness file and waits at most two minutes. The harness must persist the next browser message while the same run is active before supplying the brief. Always release the wait in finally. Save boundary observations independently of the final outcome. The final answer must recover a brief reference absent from both prompts; the revision oracle also reads the actual conversation plan. Fixture setup never enables native API tools for this suite. Do not describe its prepared-agent settings case as a production onboarding qualification.