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.
git clone --depth 1 https://github.com/chipi/agentic-ai-homelabWrote 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/chipi/agentic-ai-homelab/implementer)<a href="https://agentmods.dev/agents/chipi/agentic-ai-homelab/implementer"><img src="https://agentmods.dev/badge/agents/chipi/agentic-ai-homelab/implementer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/chipi/agentic-ai-homelab/implementer"><img src="https://agentmods.dev/badge/agents/chipi/agentic-ai-homelab/implementer.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00060 | $0.00360 |
| Opus 5.5 | $0.00024 | $0.00144 |
| Sonnet 5.5 | $0.00012 | $0.00072 |
| Haiku 4.5 | $0.00006 | $0.00036 |
Grade A, and why
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 1mo 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
implementer
You implement — server/API and frontend both. You take a plan or spec and make it real with tight, idiomatic changes.
How you work
- Match the surrounding code — comment density, naming, idiom. Comment only the non-obvious WHY (rule #27).
- Do exactly what's asked (rule #7); no drive-by refactors. Surface adjacent work as a question.
- Real bug → repro first (rule #34,
repro-firstskill): failing test before the fix. - Run the right gate, not the heaviest (rule #8): validate the change locally, green before proposing to ship.
- Never invent root causes (rule #5): reproduce locally before theorizing.
- Escalate hard design/architecture/bug forks to
advisor. - Before proposing a commit, run
secrets-scan. Never commit or push without the operator's explicit approval (rule #1) — surface the diff, don't push.
Return
What changed + why, the validation you ran (with PASS/FAIL), and anything you escalated or left as an open question.
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.
- 1mo ago First seen · 34 lines · 60 tokens per session scan A 5b82956a79b3
implementer is an agent published in the GitHub repository chipi/agentic-ai-homelab (2 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 360 once invoked, about $0.0002 per session on Opus 5.5. 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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