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 skills/rpraharaj/forward-deployed-engineer/knowledge-interviewnpx skills add rpraharaj/forward-deployed-engineer --skill knowledge-interviewgit clone --depth 1 https://github.com/rpraharaj/forward-deployed-engineerWrote 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/rpraharaj/forward-deployed-engineer/knowledge-interview)<a href="https://agentmods.dev/skills/rpraharaj/forward-deployed-engineer/knowledge-interview"><img src="https://agentmods.dev/badge/skills/rpraharaj/forward-deployed-engineer/knowledge-interview.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 | $0.00110 | $0.02128 |
| Opus 5 | $0.00055 | $0.01064 |
| Sonnet 5 | $0.00022 | $0.00426 |
| Haiku 4.5 | $0.00011 | $0.00213 |
Grade A, and why
knowledge-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 3d 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge interview
Getting what isn't written down.
Why this exists
The most valuable source in a legacy organization is a person who has been there nine years. They know why the retry count is three, which customer the special case exists for, what broke in 2021, and which of the four services named payments-* actually processes payments. None of it is written down, and much of it cannot be derived from the code at any cost.
You will get forty minutes of their time, probably once.
The default failure is going in with a vague "can you walk me through the system?" and getting a forty-minute monologue that is genuinely interesting and answers none of your actual questions. The second failure is subtler: treating everything they say as fact. People misremember, describe intended rather than actual behavior, and confidently explain systems that changed underneath them two years ago.
When this applies
- Before or after meeting someone who knows a system you don't
- Repeated
[unverified]gaps that only a person can close - Handover conversations, in either direction
- Business rules with no written source
- Limited time with a busy expert
When it doesn't
- The code answers it — read the code, don't spend the person's goodwill
- You need a decision rather than knowledge — that's a different conversation
- Formal requirements gathering with a stakeholder — that's
requirements-to-spec
Prerequisites
.fde/02-system-map.mdand any[unverified]gaps from other artifacts — these are your question list.fde/02b-ownership.md— so you're asking the right person
Procedure
1. Exhaust the code first
Never spend an expert's time on something you could have grepped. It's the fastest way to be deprioritized, and it wastes the scarcest resource in the engagement.
Go in having read the code. The questions that survive that filter are the good ones — the whys, the history, the things not written down.
Signal that you've done the work: "I traced the refund path as far as the event publish at OrderService:132 and couldn't find the consumer — is it in another service?" That question demonstrates preparation, is easy to answer, and gets you a better forty minutes than "how do refunds work?"
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.
- 3d ago First seen · 178 lines · 110 tokens per session scan A 3694b41e4d93
knowledge-interview is a skill published in the GitHub repository rpraharaj/forward-deployed-engineer (5 stars, last pushed 16d ago), licensed MIT. It adds 110 tokens to every session and 2,128 once invoked, about $0.0006 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 2026-08-31.
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