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/movebrickschi/harness-engineering-mcp/subagent-driven-developmentnpx skills add movebrickschi/harness-engineering-mcp --skill subagent-driven-developmentgit clone --depth 1 https://github.com/movebrickschi/harness-engineering-mcpWhat 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 | $0.00038 | $0.01172 |
| Opus 5 | $0.00019 | $0.00586 |
| Sonnet 5 | $0.00008 | $0.00234 |
| Haiku 4.5 | $0.00004 | $0.00117 |
Grade A, and why
subagent-driven-development 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 2d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subagent-Driven Development
Execute plan by dispatching fresh subagent per task, with code review after each.
Core principle: Fresh subagent per task + review between tasks = high quality, fast iteration
Overview
vs. Executing Plans (parallel session):
- Same session (no context switch)
- Fresh subagent per task (no context pollution)
- Code review after each task (catch issues early)
- Faster iteration (no human-in-loop between tasks)
When to use:
- Staying in this session
- Tasks are mostly independent
- Want continuous progress with quality gates
When NOT to use:
- Need to review plan first (use executing-plans)
- Tasks are tightly coupled (manual execution better)
- Plan needs revision (brainstorm first)
The Process
1. Load Plan
Read plan file, create TodoWrite with all tasks.
2. Execute Task with Subagent
For each task:
Dispatch fresh subagent:
Task tool (general-purpose):
description: "Implement Task N: [task name]"
prompt: |
You are implementing Task N from [plan-file].
Read that task carefully. Your job is to:
1. Implement exactly what the task specifies
2. Write tests (following TDD if task says to)
3. Verify implementation works
4. Commit your work
5. Report back
Work from: [directory]
Report: What you implemented, what you tested, test results, files changed, any issues
Subagent reports back with summary of work.
3. Review Subagent's Work
Dispatch code-reviewer subagent:
Task tool (superpowers:code-reviewer):
Use template at requesting-code-review/code-reviewer.md
WHAT_WAS_IMPLEMENTED: [from subagent's report]
PLAN_OR_REQUIREMENTS: Task N from [plan-file]
BASE_SHA: [commit before task]
HEAD_SHA: [current commit]
DESCRIPTION: [task summary]
Code reviewer returns: Strengths, Issues (Critical/Important/Minor), Assessment
4. Apply Review Feedback
If issues found:
- Fix Critical issues immediately
- Fix Important issues before next task
- Note Minor issues
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.
- 2d ago First seen · 190 lines · 38 tokens per session scan A 5e1f703068c2
subagent-driven-development is a skill published in the GitHub repository movebrickschi/harness-engineering-mcp (2 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 1,172 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 2026-08-31.
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brainstorming
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auto-perf-optimize
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
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