Add or extend Paperclip end-to-end evaluations that exercise real browser workflows across the server, database, and runner. Define expected outcomes, check independent evidence, and connect results to the existing reporting pipeline for local or Daytona execution.
中文简介正在准备中。当前显示英语简介。
Add or extend a Paperclip full-stack runner E2E workflow, fixture, matcher, or report evidence path for local or Daytona execution.
安装前可以查看交给 AI 代理的指令内容。
Use this skill for Product E2E Evals: real Chromium, Paperclip server, database, runner, provider, and optionally Daytona. Everyday Workflows are in this family even when their packaged results are imported into Evalbook. Runner protocol cases against the mock control plane belong in add-runner-eval.
Locate the repository using PAPERCLIP_ROOT when supplied, or
git rev-parse --show-toplevel from a checkout. From outside Git, inspect
workspace roots such as ~/paperclipai/paperclip; verify the selected root
contains tests/runner-e2e and packages/paperclip-runner. Run commands from
that repository root. The copied skill may live outside the checkout.
Read doc/evals.md, then the authoritative
tests/runner-e2e/README.md, FIXTURES.md, SECURITY.md, and
EVERYDAY-WORKFLOWS.md for the selected area. Inspect the nearest existing
catalog entry, case, harness flow, matcher, evidence writer, and report test
before changing anything. Keep the user journey on production browser/API
surfaces; do not add private runner hooks or direct fixture database writes.
Define one bounded workflow with a clear user outcome, durable state assertions, and independent evidence. Declare profile, environment, expected provider turns, timeout, cleanup, screenshots, artifact checks, and billing scope. Keep credentials and secrets out of catalog data, screenshots, fixture metadata, logs, and tracked files. Daytona images must be immutable digest references. Use the existing result validator, failure classifier, screenshot policy, and Product E2E report pipeline rather than duplicating them.
Register the workflow in tests/runner-e2e/catalog.ts and the relevant
fixture-registry.ts paths. Everyday cases and actions live in
everyday-cases.ts and everyday-flow.ts; match the existing suite's structure.
Wire its
profile/environment/case IDs through existing selector and matcher tables, and
add report/catalog coverage tests where the surrounding suite does so. Calibrate
new grading assertions with a valid outcome and a plausible wrong outcome;
missing evidence must not produce a pass. Confirm
discovery before running it:
pnpm test:e2e:runner -- --list --suite <suite-name>
pnpm test:e2e:runner -- --list --suite everyday-workflows
--all intentionally excludes the manual everyday-workflows suite and other
explicit-only cells. Use the exact suite or execution ID for those. The Product
E2E generator is pnpm test:e2e:runner:report; an Everyday Workflows result may
also be imported into Evalbook with its canonical importer, but it remains a
Product E2E run and should use its packaged dashboard/report first.
Run credential-free checks first:
pnpm test:e2e:runner:typecheck
pnpm test:e2e:runner:unit
pnpm test:e2e:runner -- --list
For an authorized live check, use the smallest explicit local --id selector.
Select Daytona only with the configured immutable image and credentials. A
full --all campaign is paid and is for the governed workflow. Verify results
from the packaged attempt evidence and dashboard; passing model-authored tests
cannot override the independent oracle.
Classify a completed wrong workflow as product or model/provider behavior as the assertions warrant. Startup, transport, and timeout symptoms require evidence-based attribution: they may indicate a Paperclip/Runner product bug, provider behavior, or infrastructure. Preserve the observed failure and cause separately, keep the existing machine grade/classifier unchanged, and retain partial attempts, retries, source SHA, catalog/definition digest, model/profile, environment, grader version, timing, tokens, runtime estimates, and cost coverage. Do not claim qualification from a partial/manual selection.
Update README.md, FIXTURES.md, SECURITY.md, or
EVERYDAY-WORKFLOWS.md when their authoritative contract changes, and link
from doc/evals.md. Do not recreate Evalbook HTML or publish raw trusted
traces, videos, archives, databases, workspaces, credentials, SVG, provider
session IDs, or hidden reasoning. Public sanitized fixture conversation, marked
screenshots, and allowlisted structured evidence are expected when the existing
publisher permits them.
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Add or extend Paperclip Runner evaluations that test real sessions against a mock control service. Define observable pass conditions, validate cases and run selections, and retain source revisions, evidence, and costs for authorized live runs.
中文简介正在准备中。当前显示英语简介。
Use a real browser to verify web pages and apps through short, supervised interactions. Capture screenshots, inspect errors and network requests, and document reproducible steps for UI bugs or expected behavior checks.
中文简介正在准备中。当前显示英语简介。
Read email linked to assigned Paperclip tasks, send new messages or replies through an assigned AgentMail inbox, and check delivery outcomes. Follow task permissions and preserve retry identifiers to avoid duplicate sends.
中文简介正在准备中。当前显示英语简介。
Inspect proposed changes in GitHub, GitLab, or Perforce for review feedback, failed automated checks, and incomplete descriptions. It separates actionable findings from informational or resolved comments, then helps fix issues and close addressed review threads when requested.
中文简介正在准备中。当前显示英语简介。
Create an AI agent company or team package from an idea or an existing repository. Define roles, reporting lines, skills, and work handoffs, then generate structured files that follow the Agent Companies specification.
中文简介正在准备中。当前显示英语简介。
Records an agent’s brief, unfiltered complaints about tools, permissions, or working conditions in Paperclip. It preserves the reaction without requiring a diagnosis or solution, then lets the agent continue its main task.
中文简介正在准备中。当前显示英语简介。