Write or revise a Paperclip plan that states the intended outcome, constraints, approach, and success checks. Capture unresolved decisions, maintain the saved plan, and request approval when the work requires it.
Write or revise a useful Paperclip plan with a clear outcome and verification. Use when a plan is requested or uncertainty needs resolving before execution.
Review the instructions the agent will receive before you install.
Plan only as much as the work needs. If execution is authorized and the next step is small and clear, do it. A request for a plan alone does not require child tasks or a new approval gate.
Describe the intended outcome, relevant constraints, chosen approach, and how to verify success. Include uncertainties or decisions that affect execution. Use the user's preferred format; keep implementation steps within one owner's task unless another owner, useful parallel output, dependency, or independent review warrants separate work.
Save a requested plan as the issue document with key plan. Update its current
revision instead of duplicating it, and link the saved document in your response.
Use the native document tools when available; legacy agents follow the paperclip
skill's document and planning API mechanics.
Respect planning mode and explicit approval requests. When approval is required,
request confirmation of the latest plan revision and wait for that decision.
After acceptance, execute cohesive work on the current ordinary task. Use
paperclip-converting-plans-to-tasks when delegation is justified.
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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.
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.
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.
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.
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.
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.