Execute implementation plans in batches with review checkpoints
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Execute plans in controlled batches with verification gates.
"I'm using the Executing Plans skill to implement this plan."
Load Plan → Review → Execute Batch → Report → Feedback → Next Batch
Default batch size: 3 tasks
For each task:
in_progresscompletedAfter each batch:
## Batch Complete
**Implemented:**
- Task 1: [summary]
- Task 2: [summary]
- Task 3: [summary]
**Verification:**
\`\`\`
[test output]
\`\`\`
Ready for feedback.
Based on feedback:
🛑 Stop immediately when:
Ask for clarification. Don't guess.
Before marking ANY task complete:
No "should work" or "looks good" - actual verification output.
### Batch N Complete
| Task | Status | Verification |
|------|--------|--------------|
| Task X | ✅ | 12/12 tests pass |
| Task Y | ✅ | Build successful |
| Task Z | ⚠️ | Needs review |
**Next batch:** Tasks A, B, C
Continue?
After all tasks:
finishing-branch skill if applicableNo reviews yet. Tell others what you thought.
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Complete methodology for preventing AI hallucinations. Use when accuracy is critical and you need Claude to verify before claiming, cite before asserting, and admit uncertainty instead of guessing.
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Transform rough ideas into solid designs through structured questioning
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Canvas API Connection Skill
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Forces every code-related claim to include file:line citations. No citation means the claim must be verified or removed. Use when building documentation, writing code reviews, or any output that others will rely on.
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Assign confidence scores (0-100) to every claim in a response. Helps users understand which parts are verified facts and which are educated guesses. Use when the user needs to know how much to trust each part of the answer.
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Forces Claude to extract exact quotes from files before making claims about them. Prevents hallucinations by grounding every statement in actual text from the codebase. Use when working with large files or unfamiliar code.
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