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 mycelium-hq/ai-brain-starter --skill interview-megit clone --depth 1 https://github.com/mycelium-hq/ai-brain-starterWrote 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/mycelium-hq/ai-brain-starter/interview-me)<a href="https://agentmods.dev/skills/mycelium-hq/ai-brain-starter/interview-me"><img src="https://agentmods.dev/badge/skills/mycelium-hq/ai-brain-starter/interview-me/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/mycelium-hq/ai-brain-starter/interview-me"><img src="https://agentmods.dev/badge/skills/mycelium-hq/ai-brain-starter/interview-me.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 | $0.00113 | $0.02646 |
| Opus 5 | $0.00056 | $0.01323 |
| Sonnet 5 | $0.00023 | $0.00529 |
| Haiku 4.5 | $0.00011 | $0.00265 |
Grade A, and why
interview-me 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 11d 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.
This is a copy
81% identical to interview-me — 63 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview Me
Cherry-picked from addyosmani/agent-skills (MIT) 2026-05-26.
Overview
What people ask for and what they actually want are different things. They ask for "a dashboard" because that's what one asks for, not because a dashboard solves their problem. They say "make it faster" without a number to hit.
The cheapest moment to find this gap is before any plan, spec, or code exists. Once you've started building, switching costs are real, and the user will rationalize the wrong thing into a "good enough" thing. The misfit gets locked in.
This skill closes the gap before it costs anything. It complements (does not replace) batched-options elicitation skills: this skill is for free-form interview when you don't yet know enough to offer a bounded set of choices. Use the batched-options skill when the user knows roughly what they want but needs to pick between framings; use this skill when you can't write a one-sentence statement of intent yet.
When to Use
Apply this skill when:
- The ask is missing at least one of: who the user is, why they want it, what success looks like, what the binding constraint is
- The request is conventional rather than specific ("build me X", "make it faster") and you can't unpack the convention without guessing
- You're tempted to start with assumptions you haven't surfaced
- The user hasn't said which value they're optimizing for when two reasonable ones are in tension (simplicity vs. flexibility, cost vs. speed)
- The user explicitly invokes: "interview me", "grill me", "before we start, are we sure?", "stress-test my thinking"
When NOT to use:
- The ask is unambiguous and self-contained ("rename this variable", "fix this typo")
- The user has explicitly asked for speed over verification
- Pure information requests ("how does X work?", "what does this code do?")
- Mechanical operations (renames, formats, file moves)
- You already have ≥95% confidence; re-read the stop condition below before assuming you don't
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.
- 11d ago First seen · 183 lines · 113 tokens per session scan A 2f47a461936d
interview-me is a skill published in the GitHub repository mycelium-hq/ai-brain-starter (36 stars, last pushed today), licensed MIT. It adds 113 tokens to every session and 2,646 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to interview-me, differing in 63 lines, and is treated as a copy.
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claudeai-sync
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tg-slot
Free a membership slot so a Telegram account can join or create a group. Accounts have a hard ceiling on channels plus supergroups, and at the ceiling both creating and joining fail with an error that misleadingly blames the target chat. Finds the least-valuable current memberships, proposes what to leave, and retries…
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tg-post
Publish a vetted post to one of your own Telegram channels or supergroups over the MCP connector rather than a browser, with the channel resolved strictly by id from a registry, rate-guarded and draft-first. It never posts to a chat matched by name similarity. Triggers: "/tg-post", "publish to the telegram channel".