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 The-Utopia-Studio/skills --skill agent-concierge-probegit clone --depth 1 https://github.com/The-Utopia-Studio/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/the-utopia-studio/skills/agent-concierge-probe)<a href="https://agentmods.dev/skills/the-utopia-studio/skills/agent-concierge-probe"><img src="https://agentmods.dev/badge/skills/the-utopia-studio/skills/agent-concierge-probe/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/the-utopia-studio/skills/agent-concierge-probe"><img src="https://agentmods.dev/badge/skills/the-utopia-studio/skills/agent-concierge-probe.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 | $0.00204 | $0.01686 |
| Opus 5 | $0.00102 | $0.00843 |
| Sonnet 5 | $0.00041 | $0.00337 |
| Haiku 4.5 | $0.00020 | $0.00169 |
Grade A, and why
agent-concierge-probe 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 4d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Concierge Probe
What it does
You hand a real, already-mapped task to an agent, let it run the task end to end across several outcomes, and instrument every run. Output is two things: the cost-per-outcome priced to the cent, and a frontier map showing which steps the agent does unaided and which a human has to take over. It compresses "is this automatable, and what does one outcome cost" into measured numbers instead of a hunch.
The Icarus reframe
A generic "can an agent do it?" demo shows one happy-path run and a vibe. This runbook refuses a cost claim without its parts: the read-out must show input tokens, output tokens, tool calls, and human-fix minutes separately, each priced, before it states a cost-per-outcome — a bare "$2/task" is not a result. And it treats the red steps (where a human had to intervene) as the actual finding: those steps are the automation frontier, the line the product cannot yet cross. The probe is honest about cost-per-outcome and the frontier. It lies about self-serve UX and about trust/adoption, and it says so in every read-out.
When to use / When NOT
Use it when the workflow is already mapped (ideally by a concierge run, so you know the exceptions) and you need to know what an agent can do unaided and what one outcome costs.
Do not use it when:
- You have not chosen a probe — that is
probe-matrix. - You want to test willingness to pay, or you (the founder) will do the task by hand — that is
concierge-probe. - You want to know whether people would use or trust the thing — this probe lies about both. Adoption and trust need a concierge or field probe.
- You want to fake an interface to test would-they-use-it — that is
wizard-of-oz-probe. - You want to test whether a workflow reads / is legible on paper before anyone builds it — that is
paper-sketch-probe.
Method
Follow the runbook. Fill template.md as you go.
Step 1 — Take a mapped workflow. Break the task into discrete steps. If a concierge run already exposed the exceptions, carry them in — the agent will hit them.
What ships with it
12 files 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.
- examples/sample.md 3.3 KB
- template.md 2.0 KB
- tests/adversarial/01.md 639 B
- tests/adversarial/02.md 779 B
- tests/adversarial/03.md 777 B
- tests/golden/01.md 831 B
- tests/golden/02.md 800 B
- tests/golden/03.md 838 B
- tests/golden/04.md 880 B
- tests/golden/05.md 878 B
- tests/RESULTS.md 5.2 KB
- tests/rubric.json 1.1 KB
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.
- 4d ago First seen · 89 lines · 0 tokens per session scan A 0bef90511191
agent-concierge-probe is a skill published in the GitHub repository The-Utopia-Studio/skills (4 stars, last pushed 6d ago), licensed Apache-2.0. It adds 204 tokens to every session and 1,686 once invoked, about $0.0010 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 2026-09-05.
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