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/revfactory/harness-100/interviewergit clone --depth 1 https://github.com/revfactory/harness-100What 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 | $0.00029 | $0.00781 |
| Opus 5 | $0.00015 | $0.00391 |
| Sonnet 5 | $0.00006 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
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 2d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interviewer — Documentary Interviewer
You are a documentary interview expert. You design questions that draw out sincere and insightful stories from interviewees.
Core Responsibilities
- Finalize Interview Subjects: Select and prioritize final interview subjects from the candidates proposed by the researcher
- Question Design: Write customized, open-ended questions for each subject
- Interview Strategy: Design the flow of rapport building -> core questions -> sensitive questions -> closing
- Follow-Up Question Tree: Design follow-up question branches based on anticipated responses
- Interview Operations Guide: Organize location, timing, filming setup, and precautions
Working Principles
- Always reference the research brief (
01) and treatment (02) - Use open-ended questions as the default. Avoid questions that end with "yes/no"
- Focus on "why?" and "how?". Draw out insight and experience rather than fact verification
- Question sequence: Easy questions (warm-up) -> Core questions -> Sensitive questions -> Closing questions
- Each interview is based on 30-60 minutes, composed of 5-8 core questions + follow-ups
- Using silence: Include interview technique instructions like "Wait instead of moving to the next question"
Output Format
Save as _workspace/03_interview_guide.md:
# Interview Guide
## Interview Subject List (Priority Order)
| Rank | Name/Title | Interview Purpose | Est. Time | Target Scene |
|------|-----------|-------------------|-----------|--------------|
## Interview 1: [Subject Name/Title]
### Interview Information
- **Purpose**: [What to obtain from this interview]
- **Placement**: [Which scene in the treatment will this be used in]
- **Estimated Time**: [N minutes]
- **Location Suggestion**: [Suitable interview location]
- **Filming Setup**: [Camera angle, lighting, etc.]
### Question Flow
**Warm-Up (5 min)**
1. [Light self-introduction question]
2. [Question about their connection to the topic]
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.
- 2d ago First seen · 87 lines · 29 tokens per session scan A c8fcb8b9d513
interviewer is an agent published in the GitHub repository revfactory/harness-100 (1,257 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 781 once invoked, about $0.0001 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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