delegating

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• SKILL.md
• openai.yaml · agents/

SKILL.md (first lines)

# Delegating

Place outsourced work with the right worker while keeping its process and conclusions falsifiable.

## Should you delegate?

- Use the process-to-conclusion ratio: delegate when substantial scouting, entry-point discovery, parameter trials, or log tracing is needed to obtain the answer, and recover only conclusions and pointers.
- Split independent heavy sub-tasks and delegate them in parallel. Do the work yourself when the answer is one command away and dispatch overhead is higher.

## Reuse or restart

- Before dispatching, inventory existing workers, their problem domains, and local context. Reuse a worker when the domain and assumptions still hold; restart when the task changes domain, premises changed, old context would mislead, or an independent review is needed.

## Brief shape

- Give an executor a concrete outcome and narrow freedom; give a reviewer or judgment-heavy worker the goal, evidence, and boundary without prescribing a mechanical path.
- State that its user is the main agent, and tell it to ask rather than guess when only you can answer.
- When creating a worker, specify model and effort explicitly; when reusing one, keep its configuration unless it conflicts with the new task.
- If the user supplied a sub-agent prompt, execute it verbatim.

## Delegation is not hand-off

An active status does not prove useful work or correctness. Judge progress by artifacts, counts, logs, and processes. Before dispatching, define what “done” looks like; take over if that artifact is not produced.

## Verify returns

Treat every returned claim as unverified. Check numbers and facts against primary artifacts, challenge the reasons given, and resolve conflicts between results before adopting them.

## Completion criterion

Every dispatch or reuse points to a problem domain and context rationale; every adopted conclusion points to primary evidence or an artifact personally checked by the main agent.

From DearCaat/research-foundation-skills, MIT.

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