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.
npx skills add isvlasov/rageatc-oss --skill evaluating-as-usergit clone --depth 1 https://github.com/isvlasov/rageatc-ossWrote 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/skills/isvlasov/rageatc-oss/evaluating-as-user)<a href="https://agentmods.dev/skills/isvlasov/rageatc-oss/evaluating-as-user"><img src="https://agentmods.dev/badge/skills/isvlasov/rageatc-oss/evaluating-as-user/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/skills/isvlasov/rageatc-oss/evaluating-as-user"><img src="https://agentmods.dev/badge/skills/isvlasov/rageatc-oss/evaluating-as-user.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 | $0.02218 |
| Opus 5 | $0.00017 | $0.01109 |
| Sonnet 5 | $0.00007 | $0.00444 |
| Haiku 4.5 | $0.00003 | $0.00222 |
Grade A, and why
evaluating-as-user 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 9d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evaluating as a User
Methodology and judgement for evaluating a running product as a real user would: derive what to test from the PRD, structure the evaluation, assess quality dimensions, format findings. Covers what to evaluate and how to think about quality — browser mechanics are in playwright-cli (preloaded); agent role, inputs, status codes, and handoff are in the agent definition.
Applies to: web applications, CLI tools, APIs. Not covered: source code review (reviewing-code), automated test generation, accessibility audits (WCAG), performance benchmarking.
Workflow
Step 1: Derive user journeys from the PRD
Read the PRD. For each P0 requirement, derive one user journey using this structure:
| Field | Description |
|---|---|
| Starting point | Where the user begins (URL, command, state) |
| Actions | Step-by-step sequence the user would take |
| Observable outcome | What confirms the requirement is satisfied |
How to derive actions: Treat the requirement as a goal, not a task. Ask: what would a person with this goal actually do? Start from the entry point a new user would reach, not the most direct technical path.
Priority: P0 requirements first. Add P1 journeys only if time permits after all P0 journeys and universal checks are complete.
Non-web projects: For CLI tools, the starting point is the terminal and the actions are command sequences. For APIs, the starting point is an endpoint and the actions are the sequence of requests a user of the API would make. The journey structure is the same.
Step 2: Run PRD-derived journeys
Attempt each derived journey in sequence. As you go:
- Execute each action in the journey
- Record what you observe at each step in
walkthrough.md(what you did, what you expected, what you saw) - Take a screenshot at each meaningful state transition (web projects)
- Note any friction, confusion, missing feedback, or failure
When a journey succeeds, note which quality dimensions (Step 4) were satisfied or strained along the way. When a journey fails, record at what step and what the failure was.
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.
- 9d ago First seen · 162 lines · 35 tokens per session scan A 3e4da202c7bd
evaluating-as-user is a skill published in the GitHub repository isvlasov/rageatc-oss (9 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 2,218 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 2026-08-31.
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