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 bobadilla-tech/requiems-api-skills --skill random-user-get-random-usergit clone --depth 1 https://github.com/bobadilla-tech/requiems-api-skillsWrote 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/bobadilla-tech/requiems-api-skills/random-user-get-random-user)<a href="https://agentmods.dev/skills/bobadilla-tech/requiems-api-skills/random-user-get-random-user"><img src="https://agentmods.dev/badge/skills/bobadilla-tech/requiems-api-skills/random-user-get-random-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/bobadilla-tech/requiems-api-skills/random-user-get-random-user"><img src="https://agentmods.dev/badge/skills/bobadilla-tech/requiems-api-skills/random-user-get-random-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 | $0.00015 | $0.00390 |
| Opus 5 | $0.00008 | $0.00195 |
| Sonnet 5 | $0.00003 | $0.00078 |
| Haiku 4.5 | $0.00002 | $0.00039 |
Grade A, and why
random-user-get-random-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 2d 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.
What it actually says
Endpoint
GET https://requiems.xyz/v1/technology/random-user
Get Random User
Returns a randomly generated fake user profile.
Response Example
{
"data": {
"name": "Grace Lopez",
"email": "[email protected]",
"phone": "555-123-4567",
"address": {
"street": "4821 Maple Avenue",
"city": "North Judyton",
"state": "California",
"zip": "94103",
"country": "United States of America"
},
"avatar": "https://api.dicebear.com/9.x/identicon/svg?seed=Grace+Lopez"
},
"metadata": {
"timestamp": "2026-01-01T00:00:00Z"
}
}
Response Fields
| Field | Type | Description |
|---|---|---|
name |
string | Full name of the generated user |
email |
string | Email address of the generated user |
phone |
string | Phone number of the generated user |
address.street |
string | Street address |
address.city |
string | City name |
address.state |
string | State or region |
address.zip |
string | Postal / ZIP code |
address.country |
string | Country name |
avatar |
string | URL to a unique identicon avatar for the generated user (DiceBear) |
Errors
undefined500 — Internal server error
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.
- 2d ago First seen · 58 lines · 15 tokens per session scan A 8d4940c1a82c
random-user-get-random-user is a skill published in the GitHub repository bobadilla-tech/requiems-api-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 15 tokens to every session and 390 once invoked, about $0.0001 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 2026-09-08.
Other skills, from other repositories
archetype-lint
This skill should be used when the user asks to "lint an archetype", "validate an archetype", "check archetype compliance", "check archetype rules compliance", or "run archetype rules". Applies 24 normative lint rules with ERROR/WARNING/INFO severity. Supports STRICT and PERMISSIVE modes. Reports violations only — it…
speckit.tester
Test Runner & Coverage - Create test plans, write tests, report coverage.
speckit.uat
UAT Analyzer - Analyze manual acceptance results and process gaps from the User.
offensive-fuzzing
Practical offensive fuzzing methodology covering target identification, fuzzer selection (AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller), harness writing, corpus curation, mutation strategies, coverage measurement, and crash triage. Use when setting up or running fuzz campaigns against any target: file parsers…
create-test-plan
Analyze what changed and generate a structured test plan at .turbo/test-plans/ .md covering four escalating levels: basic functionality, complex operations, adversarial testing, and cross-cutting scenarios. Use when the user asks to "create a test plan", "plan tests", "what should I test", "generate test scenarios"…
agent-ready-cloudflare
Audit and improve website readiness for AI agents using the Cloudflare "Is It Agent Ready?" scanner (isitagentready.com). Covers scanning via API, interpreting results, generating implementation prompts, and fixing every check. Use when the user mentions "agent ready", "isitagentready", "AI agent scan", "agent…