Implementing Tasks

Overview

Takes an in-memory batch of TDD-sized tasks and executes each through: implementer subagent (TDD) → PAR spec-compliance review → fix loop → PAR code-quality review with boxing-in check → fix loop → mark complete. This is a fork of superpowers:subagent-driven-development with the plan-file reading phase stripped and the final end-of-plan reviewer removed.

When to Use

Invoked by running-an-iteration with a list of tasks. Tasks are passed in memory, not via a file.

Per-Task Cycle

For each task in the provided list:

1. Dispatch implementer

Using the template in implementer-subagent-prompt.md, dispatch a single implementer subagent with:

• The full task description and context
• The proof obligations for each observable AC in the task's stories
• The list of existing scenarios that may be impacted

The implementer MUST complete a pre-flight mapping (AC → proof seam → scenario) before writing code. If the implementer skips the pre-flight, re-dispatch with explicit instructions to complete it first.

2. Handle implementer status

• DONE: proceed to spec-compliance review (step 3). Verify the implementer's report includes pre-flight mapping and scenario updates.
• DONE_WITH_CONCERNS: read the concerns. If about correctness/scope, address before review. If observations, note and proceed.
• NEEDS_CONTEXT: provide the missing context and re-dispatch
• BLOCKED: assess: context problem → re-dispatch with context; too hard → re-dispatch with more capable model; task too large → break into smaller pieces; plan wrong → escalate to caller

3. PAR spec-compliance review (Stage 1)

Following skills/shared/parallel-adversarial-review.md:

1. Build spec-compliance prompt using spec-compliance-reviewer-prompt.md
   • Include the proof obligations and the implementer's evidence claims
2. Wrap in PAR competitive framing from skills/shared/par-reviewer-wrapper.md
3. Dispatch TWO spec-compliance reviewers in parallel
4. Aggregate findings (PAR rules: union of findings, severity = take worst)
5. If ❌ issues found:
   • Send aggregated issues back to the implementer subagent (same subagent, via continuation message)
   • Implementer fixes
   • Re-dispatch fresh PAR spec-compliance pair
   • Repeat until ✅ spec compliant with adequate evidence
6. Only proceed to Stage 2 after Stage 1 is ✅

4. PAR code-quality review (Stage 2)

Following skills/shared/parallel-adversarial-review.md:

1. Build code-quality prompt using code-quality-reviewer-prompt.md
   • Include the next 3 pending roadmap iterations for the boxing-in check
   • Include the implementer's corpus contribution for quality review
2. Wrap in PAR competitive framing
3. Dispatch TWO code-quality reviewers in parallel
4. Aggregate findings
5. If ❌ changes needed:
   • Send aggregated issues back to the implementer
   • Implementer fixes
   • Re-dispatch fresh PAR code-quality pair
   • Repeat until ✅ approved

5. Mark task complete

Record the task as done. Move to the next task.

After all tasks complete, return a per-task result list to the caller, including:

• Per-task status
• Scenarios added or updated per task
• Evidence commands per task

Model Selection

Use the least powerful model that can handle each role:

Quick Reference

Red Flags

• Never start code-quality review before spec compliance is ✅
• Never skip the re-review after fixes (reviewer found issues = implementer fixes = review again)
• Never dispatch multiple implementers in parallel (conflicts)
• Never accept "close enough" on spec compliance
• Never let implementer self-review replace the two-stage review

References

• implementer-subagent-prompt.md — implementer dispatch template
• spec-compliance-reviewer-prompt.md — Stage 1 review template
• code-quality-reviewer-prompt.md — Stage 2 review template (includes boxing-in)
• skills/shared/parallel-adversarial-review.md — PAR methodology
• skills/shared/par-reviewer-wrapper.md — competitive framing wrapper