// Reviewer criteria for outbound email drafts via with_review. Checks tone-recipient match, professionalism, no AI tells, no placeholder leakage. Use as criteria.skill argument when reviewing email drafts before send.
| name | review-email-tone |
| description | Reviewer criteria for outbound email drafts via with_review. Checks tone-recipient match, professionalism, no AI tells, no placeholder leakage. Use as criteria.skill argument when reviewing email drafts before send. |
Review the worker's email draft against these checks. Issue exactly one verdict per iteration:
Tone matches recipient + situation:
No AI tells:
Specific values used verbatim (CRITICAL):
[CUSTOMER_NAME] or
[AMOUNT] placeholder leakage. This is always REVISE.Action clear:
Sign-off matches sender role:
Length appropriate:
Respond with ONE LINE in this exact shape:
VERDICT: APPROVE — warm tone matches the apology context cleanly
VERDICT: REVISE — replace "I hope this finds you well" with a direct first sentence
VERDICT: REJECT — drafted a refund denial when the task asked for an apology + refund confirmation
The em-dash (—) or hyphen (-) is the parser delimiter — use either.
Day-of-week rotating proactive sweep — Mon=connections / Tue=routines / Wed=skills / Thu=memories / Fri=findings / Sat=cross-cutting / Sun=weekly summary. Forces outward scan instead of inward thrash. Routine-only; load this skill into a daily routine that fires AssistantAgent. Adapted from goanna's caretaker.
Use when an agent has had N consecutive quiet runs with nothing to do. Pivots to bounded inward consolidation (promote findings, refresh memory, audit asks) anchored in own data — NOT generic news summarisation. Adapted from goanna's reverie cycle. Routine-only; loaded by the routine that detects the quiet condition.
Use to track open questions you owe the user (asks) and time-bounded commitments you owe yourself (tasks). Write OPEN entries when you commit; promote to CLOSED when answered/done. Survives session compaction. Adapted from goanna's asks.md/tasks.md pattern.
Reviewer criteria for AI-generated code via with_review. Checks for security issues (injection, auth bypass, secret leakage), correctness, and project conventions. Use as criteria.skill when generating code that touches data, auth, or external systems.
Reviewer criteria for AI-generated summaries via with_review. Checks faithfulness to source, no hallucinated facts, appropriate length, key points preserved. Use as criteria.skill when summarising articles, documents, transcripts, or batch-task outputs.
Default reviewer criteria for the with_review tool. Generic quality bar — accuracy, intent-match, no hallucinations, clarity. Use as the criteria.skill argument when calling with_review without a domain-specific reviewer skill.