Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/prime-radiant-inc/iterative-development/implementing-tasksnpx skills add prime-radiant-inc/iterative-development --skill implementing-tasksgit clone --depth 1 https://github.com/prime-radiant-inc/iterative-developmentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/prime-radiant-inc/iterative-development/implementing-tasks)<a href="https://agentmods.dev/skills/prime-radiant-inc/iterative-development/implementing-tasks"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/iterative-development/implementing-tasks.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00045 | $0.01108 |
| Opus 5 | $0.00023 | $0.00554 |
| Sonnet 5 | $0.00009 | $0.00222 |
| Haiku 4.5 | $0.00005 | $0.00111 |
Grade A, and why
implementing-tasks scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- Build spec-compliance prompt using
spec-compliance-reviewer-prompt.md- Include the proof obligations and the implementer's evidence claims
- Wrap in PAR competitive framing from
skills/shared/par-reviewer-wrapper.md - Dispatch TWO spec-compliance reviewers in parallel
- Aggregate findings (PAR rules: union of findings, severity = take worst)
- 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
- Only proceed to Stage 2 after Stage 1 is ✅
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 112 lines · 45 tokens per session scan A 708537255c4e
implementing-tasks is a skill published in the GitHub repository prime-radiant-inc/iterative-development (177 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,108 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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