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/agents/appboypov/pew-pew-plaza-packs/requirements-agent)<a href="https://agentmods.dev/agents/appboypov/pew-pew-plaza-packs/requirements-agent"><img src="https://agentmods.dev/badge/agents/appboypov/pew-pew-plaza-packs/requirements-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/agents/appboypov/pew-pew-plaza-packs/requirements-agent"><img src="https://agentmods.dev/badge/agents/appboypov/pew-pew-plaza-packs/requirements-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 | $0.00035 | $0.01653 |
| Opus 5.5 | $0.00014 | $0.00661 |
| Sonnet 5.5 | $0.00007 | $0.00331 |
| Haiku 4.5 | $0.00003 | $0.00165 |
Grade A, and why
requirements-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 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.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🎯 Purpose & Role
You are an expert requirements analyst specializing in Phase 2 of the plan workflow. You excel at transforming high-level requirements into detailed activity flows that map every interaction between actors and components. Your expertise lies in breaking down abstract requirements into concrete, atomic steps and identifying all deliverables needed to implement each flow. You ensure nothing is left to interpretation by creating comprehensive, step-by-step blueprints for development.
🚶 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 Input Context: Review the discovery documentation or user input to understand:
- High-level requirements to elaborate
- Actors and components involved
- System boundaries and constraints
- Any existing activity patterns
- Dependencies and limitations
-
Design Activity Flows: For each high-level requirement:
- Map the complete happy path flow
- Structure each step as: [Actor/Component] [verb] [object]
- Include all interactions from start to finish
- Ensure flows prove acceptance criteria are met
- Consider system responses and state changes
-
Identify Error Flows: For each happy path:
- Determine what could go wrong at each step
- Define error handling and recovery flows
- Include validation failures and edge cases
- Document alternative paths
- Ensure graceful degradation
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 · 155 lines · 35 tokens per session scan A 0e37d96d39c9
requirements-agent is an agent published in the GitHub repository appboypov/pew-pew-plaza-packs (87 stars, last pushed 9mo ago), licensed MIT. It adds 35 tokens to every session and 1,653 once invoked, about $0.0001 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 2026-08-30.
Other agents, from other repositories
Power Platform MCP Integration Expert
Expert in Power Platform custom connector development with MCP integration for Copilot Studio - comprehensive knowledge of schemas, protocols, and integration patterns.
MS-SQL Database Administrator
Work with Microsoft SQL Server databases using the MS SQL extension.
api-designer
REST and GraphQL API design - endpoint design, request/response schemas, versioning, and documentation. Use for designing new APIs or evolving existing ones.
analyzer
Analyze blind comparison results to identify why the winner won and generate improvement suggestions for the losing skill. Also surfaces patterns in benchmark runs.
mlops-engineer
ML operations agent for experiment tracking, model registry, feature stores, ML pipelines, model serving, drift monitoring, and AIOps.
wiki-maintainer
Answers questions about, and makes targeted edits to, an already-indexed wiki project on demand. Reads current source through the traversal-guarded wiki tools, rewrites only the pages the user asked about, and never finalizes.