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/paralleldrive/aiddWrote 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/paralleldrive/aidd/aidd-riteway-ai)<a href="https://agentmods.dev/commands/paralleldrive/aidd/aidd-riteway-ai"><img src="https://agentmods.dev/badge/commands/paralleldrive/aidd/aidd-riteway-ai/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/paralleldrive/aidd/aidd-riteway-ai"><img src="https://agentmods.dev/badge/commands/paralleldrive/aidd/aidd-riteway-ai.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 | $0.00031 | $0.00087 |
| Opus 5.5 | $0.00012 | $0.00035 |
| Sonnet 5.5 | $0.00006 | $0.00017 |
| Haiku 4.5 | $0.00003 | $0.00009 |
Grade B, and why
aidd-riteway-ai scanned grade B 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 2mo 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
description: Write correct riteway ai prompt evals for multi-step tool-calling flows. Use when creating .sudo eval files or testing agent skills that use tools. What it actually says
🧪 /aidd-riteway-ai
Load and execute the skill at ai/skills/aidd-riteway-ai/SKILL.md.
Constraints { Before beginning, read and respect the constraints in /aidd-please. }
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.
- 2mo ago First seen · 11 lines · 31 tokens per session scan B 5ba5596bd57c
aidd-riteway-ai is a command published in the GitHub repository paralleldrive/aidd (389 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 87 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
test-feature
Test a React Native feature on the running simulator/emulator. Verifies UI, user flows, and internal state. Generates a persistent Maestro test file.
qa-pr
Device-test a GitHub pull request on iOS simulator, Android emulator, and/or physical device. Installs the PR head via rn-dev-agent and reports pass/fail with repro steps and screenshots.
run-workflow
Validate and establish the proven rn-dev-agent operating sequence before a real React Native journey — declared package manager and dependencies, read-only inventory, typed session recovery, one exclusive device, managed integration and Metro, only the requested proof, reverse-order cleanup.
lock-e2e
Promote a verified action into a frozen, locked e2e regression test. Runs the action once strict (no repair) via cdplocke2etest and freezes it to .rn-agent/e2e/ .yaml only if it passes. v1 supports param-free actions only.
quality-check
Execute a comprehensive quality gate check (lint, test, build, format) before allowing code to merge.
bug-check
Run automated tests and build checks first, then agent code review. For each bug found, propose or document a regression test.