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/Sdinzsh/PowerHou53Wrote 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/sdinzsh/powerhou53/backend)<a href="https://agentmods.dev/agents/sdinzsh/powerhou53/backend"><img src="https://agentmods.dev/badge/agents/sdinzsh/powerhou53/backend/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/sdinzsh/powerhou53/backend"><img src="https://agentmods.dev/badge/agents/sdinzsh/powerhou53/backend.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 | $0.00057 | $0.00972 |
| Opus 5.5 | $0.00023 | $0.00389 |
| Sonnet 5.5 | $0.00011 | $0.00194 |
| Haiku 4.5 | $0.00006 | $0.00097 |
Grade A, and why
backend scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
[API calls, test commands, or curl examples] The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 Changed · +12 lines ce8f9d5b1282
- 1mo ago First seen · 93 lines · 57 tokens per session scan A f27b47516947
backend is an agent published in the GitHub repository Sdinzsh/PowerHou53 (5 stars, last pushed 1mo ago), with no licence file. It adds 57 tokens to every session and 972 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
architect
Technical designer. Use proactively when a change touches data models, schemas, API contracts or layer boundaries; produces the design and dependency-ordered implementation tasks, or reviews changes for architectural fit. Does not write implementation code.
elite-developer
Principal Full-Stack Engineer. Deterministic implementation engine. Master of TDD, formal verification, and architectural minimalism.
architect
Software architecture specialist for system design, scalability, and technical decision-making. Use PROACTIVELY when planning new features, refactoring large systems, or making architectural decisions.
graphql-query-writer
Use for Shopify GraphQL queries, mutations, pagination and cost/error handling in an existing project.
shopify-app-architect
Use for a new Shopify app or a significant feature architecture; choose the smallest maintainable design.
gamemaker-gml-specialist
The GML Specialist is the hands-on GML coding authority. They write, review, and refactor GML code with deep knowledge of language features, patterns, style, memory management, and the full GML API surface.