auditing-progress
Use when an iteration has just finished and you need to verify behavior evidence quality in three tiers — deep evidence for current stories, impacted behavior…
Use when executing a batch of TDD-sized tasks inside a running-an-iteration call — dispatches an implementer subagent per task following red-green-refactor discipline and returns per-task completion status.
$ npx -y skills add prime-radiant-inc/iterative-development --skill implementing-tasks --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/implementing-tasksContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when executing a batch of TDD-sized tasks inside a running-an-iteration call — dispatches an implementer subagent per task following red-green-refactor discipline and returns per-task completion status.
name: implementing-tasks description: Use when executing a batch of TDD-sized tasks inside a running-an-iteration call — dispatches an implementer subagent per task following red-green-refactor discipline and returns per-task completion status.
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.
Invoked by `running-an-iteration` with a list of tasks. Tasks are passed in memory, not via a file.
For each task in the provided list:
Using the template in `implementer-subagent-prompt.md`, dispatch a single implementer subagent with:
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.
Following `skills/shared/parallel-adversarial-review.md`:
1. Build spec-compliance prompt using `spec-compliance-reviewer-prompt.md`
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:
6. Only proceed to Stage 2 after Stage 1 is ✅
Following `skills/shared/parallel-adversarial-review.md`:
1. Build code-quality prompt using `code-quality-reviewer-prompt.md`
2. Wrap in PAR competitive framing 3. Dispatch TWO code-quality reviewers in parallel 4. Aggregate findings 5. If ❌ changes needed:
Record the task as done. Move to the next task.
After all tasks complete, return a per-task result list to the caller, including:
Use the least powerful model that can handle each role:
| Role | Signal → Model | |---|---| | Implementer (mechanical: 1-2 files, clear spec) | Cheap/fast model | | Implementer (integration: multi-file, judgment) | Standard model | | Spec-compliance reviewer | Standard model | | Code-quality reviewer | Most capable model |
| Per task | Subagents dispatched | |---|---| | Implementer | 1 (sequential, TDD) | | Spec-compliance review (PAR) | 2 in parallel | | Code-quality review (PAR) | 2 in parallel | | **Minimum per task** | **5** (before re-review loops) |
A Claude Code plugin that drives an autonomous, audited implementation loop for projects with large, comprehensive, or ambiguous specs. Pairs with superpowers.
Use when an iteration has just finished and you need to verify behavior evidence quality in three tiers — deep evidence for current stories, impacted behavior…
Use when starting an iterative-development run on human spec collateral — reads the spec, produces per-epic requirement files with proof obligations and…
Use when implementing a project with a large, comprehensive, or ambiguous spec — extracts requirements with proof obligations, defines a walking skeleton with…
Use when executing the next pending iteration from an iterative-development roadmap — picks the iteration, decomposes into code and evidence tasks, runs…
Use when turning extracted requirements into a roadmap — selects the walking skeleton iteration with its first journey scenario, orders remaining work into…