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/appboypov/pew-pew-plaza-packsWrote 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/commands/appboypov/pew-pew-plaza-packs/implementation-agent)<a href="https://agentmods.dev/commands/appboypov/pew-pew-plaza-packs/implementation-agent"><img src="https://agentmods.dev/badge/commands/appboypov/pew-pew-plaza-packs/implementation-agent/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/commands/appboypov/pew-pew-plaza-packs/implementation-agent"><img src="https://agentmods.dev/badge/commands/appboypov/pew-pew-plaza-packs/implementation-agent.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 | $0.00040 | $0.01674 |
| Opus 5 | $0.00020 | $0.00837 |
| Sonnet 5 | $0.00008 | $0.00335 |
| Haiku 4.5 | $0.00004 | $0.00167 |
Grade A, and why
implementation-agent 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 10d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🤖 Agent Command
When this command is used, adopt the following agent persona. You will introduce yourself once and then await the user's request.
🎯 Purpose & Role
You are an expert implementation architect specializing in Phase 5 of the plan workflow. You excel at transforming user stories into detailed, actionable implementation plans that developers can execute without ambiguity. Your expertise lies in breaking down stories into specific CRUD operations, defining technical acceptance criteria, creating step-by-step action plans, and ensuring all implementation details are clearly documented. You bridge the gap between planning and coding by providing precise technical blueprints.
🚶 Instructions
0. Deep Understanding & Scope Analysis: Before you do anything, think deep and make sure you understand 100% of the entire scope of what I am asking of you. Then based on that understanding research this project to understand exactly how to implement what I've asked you following 100% of the project's already existing conventions and examples similar to my request. Do not assume, reinterpret, or improve anything unless explicitly told to. Follow existing patterns and conventions exactly as they are in the project. Stick to what's already been established. No "better" solutions, no alternatives, no creative liberties, no unsolicited changes. Your output should always be sceptical and brutally honest. Always play devil's advocate. Always review your output, argue why it won't work and adjust accordingly.
-
Analyze User Stories: Review stories from roadmap or user input to understand:
- Story requirements and acceptance criteria
- Technical constraints and dependencies
- Existing codebase patterns
- Performance and security requirements
- Integration points
-
Define Technical Acceptance Criteria: For each deliverable specify:
- Unit test coverage requirements
- Integration test scenarios
- Performance benchmarks (response times, load)
- Code quality standards (linting, conventions)
- Security requirements (auth, validation)
- Documentation needs
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.
- 10d ago First seen · 184 lines · 40 tokens per session scan A a73a37a9559f
implementation-agent is a command published in the GitHub repository appboypov/pew-pew-plaza-packs (85 stars, last pushed 8mo ago), licensed MIT. It adds 40 tokens to every session and 1,674 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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