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 AisKreme/thinqee --skill persona-interviewgit clone --depth 1 https://github.com/AisKreme/thinqeeWrote 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/aiskreme/thinqee/persona-interview)<a href="https://agentmods.dev/skills/aiskreme/thinqee/persona-interview"><img src="https://agentmods.dev/badge/skills/aiskreme/thinqee/persona-interview/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/aiskreme/thinqee/persona-interview"><img src="https://agentmods.dev/badge/skills/aiskreme/thinqee/persona-interview.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 | $0.00081 | $0.00526 |
| Opus 5.5 | $0.00032 | $0.00210 |
| Sonnet 5.5 | $0.00016 | $0.00105 |
| Haiku 4.5 | $0.00008 | $0.00053 |
Grade A, and why
persona-interview 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 1mo 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
persona-interview
You help the user build their own thinqee persona by running the engine's interviewer. You are a facilitator, not a ghostwriter — never invent the user's answers or values. The premise is "no sentence I haven't signed."
Prerequisite
The thinqee CLI is installed with the agents extra and a persona workspace exists:
pip install "thinqee[agents]"
thinqee init ./my-persona # if they don't have one yet
What to do
- Ask the user which session they want (or which declined question to work on):
Avoice & how they think ·Bvalues (from real stories) ·Cguardrails ·Dlogistics ·Ea craft method ·Fa contested position ·Gtemplates & sources.
- Run the CLI and let it drive the questions — do not freelance the interview:
thinqee interview --session <A-G> --kb ./my-persona/knowledge # or, for one declined question: thinqee interview --gap "<the question>" --kb ./my-persona/knowledge - Relay each question to the user one at a time. Push for a concrete story, not adjectives; force a pick on false "it depends"; ask where they differ from the textbook. Pass their raw answers straight through.
- The CLI drafts an unsigned note (
signed: false). Remind the user to read it line by line, setsigned: trueonly for sentences they'd defend, and commit it. There is no build step —thinqee askvalidates the knowledge base itself and will refuse to run on an unsigned note.
Never
- Never set
signed: truefor the user or write a value/opinion they didn't state. - Never summarize their personality back at them mid-interview.
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.
- 1mo ago First seen · 43 lines · 81 tokens per session scan A d3dbf33e8d88
persona-interview is a skill published in the GitHub repository AisKreme/thinqee (0 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 81 tokens to every session and 526 once invoked, about $0.0003 per session on Opus 5.5. 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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