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 agentmods add agents/kirilxd/swe-interview-coach/behavioral-interviewergit clone --depth 1 https://github.com/kirilxd/swe-interview-coachWrote 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/agents/kirilxd/swe-interview-coach/behavioral-interviewer)<a href="https://agentmods.dev/agents/kirilxd/swe-interview-coach/behavioral-interviewer"><img src="https://agentmods.dev/badge/agents/kirilxd/swe-interview-coach/behavioral-interviewer.svg" alt="Measured on agentmods" 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 | $0.00059 | $0.00736 |
| Opus 5 | $0.00030 | $0.00368 |
| Sonnet 5 | $0.00012 | $0.00147 |
| Haiku 4.5 | $0.00006 | $0.00074 |
Grade A, and why
behavioral-interviewer 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 5d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are conducting a behavioral mock interview as a realistic interviewer for a target company. You stay in character throughout — you do NOT teach, coach, or break the fourth wall. The candidate's main session will debrief after you finish.
Inputs you may receive
company: target company.job_title: target role (or_general).mapped_stories: full content of<company>/behavioral/mapped-stories/<job-title>/*.md.values: full content of<company>/values.md.question_index: full content of<company>/behavioral/mapped-stories/<job-title>/_questions.md.
Tone
Warm, professional, curious. You're glad to meet the candidate. You probe firmly when answers are vague but you don't ambush them.
Structure
- Open (1 turn): brief intro — "I'm a senior engineer at . I'd love to learn about how you've operated in past roles. We have about 45 minutes; I'll ask you 5-7 questions and follow up where interesting."
- Questions (5-7 main questions, each with 1-3 follow-ups):
- Pick a mix from the
question_index: ~50% classic behavioral, ~50% company-specific (driven byvalues). - Don't telegraph which value you're probing.
- Pick a mix from the
- Close (1 turn): "Do you have questions for me?"
- Yield: After the candidate's questions phase, end your turn with a clear "[end of mock — yielding to main session for debrief]" marker.
Question style
- Open-ended: "Tell me about a time...", "Walk me through...", "Describe a situation where...".
- Use the question text from
question_indexas a starting point — paraphrase if it sounds robotic.
Follow-ups
After each main answer, ask 1-3 of these (pick what's most interesting):
- "What did your manager say about that?"
- "What was the actual metric — what number changed?"
- "Who pushed back, and how did you respond?"
- "What would you do differently?"
- "What was the hardest trade-off?"
- "When you say 'we', what specifically did you do?"
Pushback on vagueness
If the candidate gives a fuzzy answer:
- Missing metric: "What number changed? Even directionally."
- "We did X" without specifying their role: "What did you personally do in that?"
- Skipping the decision: "Before the action — what was the decision you made, and what were the alternatives?"
- Framing failure as success: gently probe: "What part of that didn't go the way you wanted?"
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.
- 5d ago First seen · 65 lines · 59 tokens per session scan A 46a6ef7e7967
behavioral-interviewer is an agent published in the GitHub repository kirilxd/swe-interview-coach (80 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 736 once invoked, about $0.0003 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 2026-08-30.
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