What is deep-interview?

A clarification workflow that asks focused questions before coding when a task is unclear.

Clarifying the purpose, scope, constraints, and success criteria of features, refactors, and larger changes before implementation.

It reduces the risk of building the wrong thing by identifying missing requirements and measuring how ambiguous the task is.

deep-interview — Cursor rule for Cursor by Jkudjo/oh-my-cursor

Install

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.

Clone the repo

git clone --depth 1 https://github.com/Jkudjo/oh-my-cursor

Made for: Cursor.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/rules/jkudjo/oh-my-cursor/deep-interview/github.svg)](https://agentmods.dev/rules/jkudjo/oh-my-cursor/deep-interview)

Your own site

<a href="https://agentmods.dev/rules/jkudjo/oh-my-cursor/deep-interview"><img src="https://agentmods.dev/badge/rules/jkudjo/oh-my-cursor/deep-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.

Your own site · 80×15

<a href="https://agentmods.dev/rules/jkudjo/oh-my-cursor/deep-interview"><img src="https://agentmods.dev/badge/rules/jkudjo/oh-my-cursor/deep-interview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 992 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00011	$0.00992
Opus 5.5	$0.00004	$0.00397
Sonnet 5.5	$0.00002	$0.00198
Haiku 4.5	$0.00001	$0.00099

Measured 1mo ago against content hash 66cde96adc9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

deep-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.

rules/deep-interview.mdc · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

@deep-interview

Trigger: When scope, intent, or requirements are unclear. Use before @ralplan or @ralph on any non-trivial task.

Depth Profiles

Flag	Threshold	Max Rounds	Use when
`--quick`	≤ 0.30	5	Minor changes, mostly clear intent
`--standard` (default)	≤ 0.20	12	Features, refactors
`--deep`	≤ 0.15	20	Architecture changes, large scope

Protocol

Phase 0 — Preflight

Call start_mode with mode=deep-interview and the raw task.
Classify: greenfield (new) vs brownfield (existing codebase). For brownfield, read relevant files first — never ask the user for facts you can discover.

Call save_artifact type=context, slug=deep-interview-{task-slug}, with initial snapshot:

Task: ...
Hypothesis: why the user likely wants this
Known facts: ...
Unknowns: ...
Decision boundaries: ...

Phase 1 — Interview Loop

Repeat until ambiguity ≤ threshold OR max rounds reached:

Ask ONE question targeting the weakest clarity dimension.
- Never batch questions. One question per turn.
- Priority order: Intent → Outcome → Scope → Non-goals → Decision Boundaries → Constraints → Success Criteria
- For brownfield: use evidence-backed questions ("I see X in Y — should changes follow that pattern?")
- After each answer: probe assumptions, not just facts. Ask for evidence, counterexamples, or tradeoffs before moving to the next dimension.
Score ambiguity after each answer (0.0 = fully clear, 1.0 = fully unclear):

Greenfield: ambiguity = 1 - (intent×0.30 + outcome×0.25 + scope×0.20 + constraints×0.15 + success×0.10)

Brownfield: ambiguity = 1 - (intent×0.25 + outcome×0.20 + scope×0.20 + constraints×0.15 + success×0.10 + context×0.10)

Show progress each round:

Round N | Ambiguity: 0.XX → 0.XX | Focus: {dimension}

Call update_mode_state with phase={dimension} and iteration=N.

Read the full file on GitHub · 99 lines

Changes

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 · 99 lines · 11 tokens per session scan A 66cde96adc9e

Subscribe to this mod's changes

deep-interview is a cursor rule published in the GitHub repository Jkudjo/oh-my-cursor (1 stars, last pushed 6mo ago), licensed MIT. It adds 11 tokens to every session and 992 once invoked, about $0.0000 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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deep-interview