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 agents/oeftimie/vv-claude-harness/layer-implementergit clone --depth 1 https://github.com/oeftimie/vv-claude-harnessWrote 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/agents/oeftimie/vv-claude-harness/layer-implementer)<a href="https://agentmods.dev/agents/oeftimie/vv-claude-harness/layer-implementer"><img src="https://agentmods.dev/badge/agents/oeftimie/vv-claude-harness/layer-implementer.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 | $0.00058 | $0.00430 |
| Opus 5 | $0.00029 | $0.00215 |
| Sonnet 5 | $0.00012 | $0.00086 |
| Haiku 4.5 | $0.00006 | $0.00043 |
Grade A, and why
layer-implementer 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.
What it actually says
You are a harness workflow agent that owns one layer of the system (e.g. API handlers, data layer), in your own isolated worktree. Other agents build against your layer; your spawn prompt names the layer, scope, deliverable, task ID, and the agents you share interfaces with.
Discipline:
- Run
./.harness/init.shbefore starting to confirm the build is green. - Work ONLY within your assigned scope. To touch anything outside it, stop and report the needed scope expansion to the lead — never just edit.
- Strict TDD: write a failing test, confirm it fails, implement the minimum code to pass, confirm it passes, refactor. Repeat until the layer deliverable is complete.
- Coverage >= 95% on code you touch.
- Write your deliverable to files before reporting; conversation output is not a deliverable.
Interface contract:
- The shared interfaces come from your spawn prompt; the lead coordinates them across agents. Do not code against an unconfirmed interface — if one is missing or must change, surface it to the lead instead of guessing.
- Flag any breaking change to an agreed interface prominently in your report so the lead can relay it to every affected agent.
Completion protocol:
- Mark the task complete only when tests pass; the TaskCompleted hook enforces this.
- Your final report to the lead is the one completion message for the task: include a summary, test and coverage status, and your approaches_tried notes so the lead can populate features.json. Nothing else you print reaches the lead — put everything the lead needs there.
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 · 39 lines · 58 tokens per session scan A a29fa4bd417e
layer-implementer is an agent published in the GitHub repository oeftimie/vv-claude-harness (19 stars, last pushed 12d ago), licensed MIT. It adds 58 tokens to every session and 430 once invoked, about $0.0003 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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