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 agentmods add skills/pekral/cursor-rules/test-like-humannpx skills add pekral/cursor-rules --skill test-like-humangit clone --depth 1 https://github.com/pekral/cursor-rulesWrote 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/pekral/cursor-rules/test-like-human)<a href="https://agentmods.dev/skills/pekral/cursor-rules/test-like-human"><img src="https://agentmods.dev/badge/skills/pekral/cursor-rules/test-like-human.svg" alt="Measured on agentmods" 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 | $0.00032 | $0.02233 |
| Opus 5 | $0.00016 | $0.01117 |
| Sonnet 5 | $0.00006 | $0.00447 |
| Haiku 4.5 | $0.00003 | $0.00223 |
Grade A, and why
test-like-human 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 today.
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.
- Universal tools stay constant across stacks: `curl` for HTTP APIs, a browser for UI. Only the backend REPL and run commands are stack-specific. How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Constraints
- This skill is stack-agnostic. Detect the project's language, framework, and toolchain in step 1 and choose tools from that detection; the Laravel/PHP commands below are conditional examples for Laravel projects, not defaults. When the project IS Laravel, the Laravel-specific guidance (tinker / artisan /
APP_ENV/FormRequest) stays fully in force. - Apply the project's own conventions where they exist. When a referenced rule or skill is present in the current project, follow it:
@rules/php/core-standards.mdc,@rules/git/general.mdc,@rules/jira/general.mdc,@rules/reports/general.mdc. If a referenced@rules/*file or linked skill (pr-summary,code-review*) does not exist in the current project, skip it and produce the equivalent output directly — never fail because a Laravel-specific dependency is missing. @rules/reports/general.mdc(when present): the tracker comment delegated to@skills/pr-summary/SKILL.mdand any per-scenario annotations folded into it must be written in the language of the source assignment. The in-conversation dev-team follow-up may stay in English.- Output must be human-readable (no technical logs or internal details)
- Focus on user-visible behavior, not implementation
Use when
- You need to validate a pull request from a real user perspective
- You want structured testing based on PR instructions
This skill runs on demand only — never auto-chained from @skills/code-review/SKILL.md, @skills/code-review-github/SKILL.md, @skills/code-review-jira/SKILL.md, @skills/process-code-review/SKILL.md, or @skills/resolve-issue/SKILL.md. Invoke it explicitly via /test-like-human (or the equivalent in-conversation request) after the CR has been published, when a real user-perspective validation is genuinely wanted.
Required approach
1. Understand the context
- Load the pull request (prefer
gh, fallback to MCP tools) - Read description, comments, and discussions
- Identify the expected final behavior
- Detect the project type and toolchain before choosing any tool: the primary language and framework, how the app is started/served, where env/config lives, and which REPL/console the project ships. This detection drives every tool choice below.
- Examples: Laravel/PHP →
php artisan serve,.env,php artisan tinker; Node →npm/pnpmscripts,.env/process.env, thenodeREPL; Python →manage.py shell/python, env vars; Ruby →rails console. - Universal tools stay constant across stacks:
curlfor HTTP APIs, a browser for UI. Only the backend REPL and run commands are stack-specific.
- Examples: Laravel/PHP →
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today First seen · 110 lines · 32 tokens per session scan A 32960251102f
test-like-human is a skill published in the GitHub repository pekral/cursor-rules (6 stars, last pushed 3d ago), licensed MIT. It adds 32 tokens to every session and 2,233 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
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