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 curiositech/some_claude_skills --skill values-behavioral-interviewgit clone --depth 1 https://github.com/curiositech/some_claude_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/curiositech/some_claude_skills/values-behavioral-interview)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/values-behavioral-interview"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/values-behavioral-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/curiositech/some_claude_skills/values-behavioral-interview"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/values-behavioral-interview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00088 | $0.03389 |
| Opus 5 | $0.00044 | $0.01695 |
| Sonnet 5 | $0.00018 | $0.00678 |
| Haiku 4.5 | $0.00009 | $0.00339 |
Grade A, and why
values-behavioral-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 8d 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Values & Behavioral Interview
Preparation system for behavioral and values-fit interview rounds at mission-driven AI companies, with particular depth on Anthropic's approach. These rounds are NOT standard "tell me about a time" STAR interviews. They go deeper: negative framing, 5-6 layers of follow-up, genuine self-awareness testing, and mission alignment probing.
The core insight: interviewers are not listening to your story. They are listening to how you think about your story.
When to Use
Use for:
- Preparing for culture-fit or values rounds at any company
- Building a story bank with STAR-L structure (extended with Learning)
- Practicing negative-frame questions (failures, weaknesses, disagreements)
- Developing comfort with deep introspective follow-ups
- Aligning personal narrative with company mission
- Calibrating authenticity vs. preparation balance
NOT for:
- Coding interview practice (use
senior-coding-interview) - System design rounds (use
ml-system-design-interview) - Resume or CV creation (use
cv-creator) - Raw career story extraction (use
career-biographer) - Technical deep dive preparation (use
anthropic-technical-deep-dive)
Question Category Map
mindmap
root((Values Interview))
Failure & Learning
Project failures
Wrong decisions
Missed signals
Recovery process
Conflict & Disagreement
Manager disagreements
Peer conflicts
Technical debates
Escalation decisions
Mission & Motivation
Why this company
Why AI safety
Long-term vision
Personal connection
Self-Awareness & Growth
Blind spots
Feedback received
Changed opinions
Working style
Ethics & Trade-offs
Competing priorities
Uncomfortable decisions
Integrity tests
Gray areas
Ambiguity & Uncertainty
Incomplete information
Changing requirements
No right answer
Comfort with unknown
What ships with it
3 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.
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.
- 8d ago First seen · 311 lines · 88 tokens per session scan A 463b12d8cc24
values-behavioral-interview is a skill published in the GitHub repository curiositech/some_claude_skills (219 stars, last pushed 5d ago), licensed MIT. It adds 88 tokens to every session and 3,389 once invoked, about $0.0004 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 2026-09-03.
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