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 mrzhangguoguo/oh-my-workbuddy --skill deep-interviewgit clone --depth 1 https://github.com/mrzhangguoguo/oh-my-workbuddyWrote 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/mrzhangguoguo/oh-my-workbuddy/deep-interview)<a href="https://agentmods.dev/skills/mrzhangguoguo/oh-my-workbuddy/deep-interview"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/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.
<a href="https://agentmods.dev/skills/mrzhangguoguo/oh-my-workbuddy/deep-interview"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/deep-interview.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00024 | $0.04033 |
| Opus 5 | $0.00012 | $0.02017 |
| Sonnet 5 | $0.00005 | $0.00807 |
| Haiku 4.5 | $0.00002 | $0.00403 |
Grade A, and why
deep-interview scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ported from oh-my-codex
deep-interview. OMX runtime conventions ($macroinvocation,omxCLI,.omx/state directory) are replaced with WorkBuddy idioms (Skill tool, Agent tool, task list,.workbuddy/memory).
<Use_When>
- The request is broad, ambiguous, or missing concrete acceptance criteria.
- The user says "deep interview", "interview me", "ask me everything", "don't assume", or "ouroboros".
- The user wants to avoid misaligned implementation from underspecified requirements.
- You need a requirements artifact before handing off to
plan,team, or an execution workflow. </Use_When>
<Do_Not_Use_When>
- The request already has concrete file/symbol targets and clear acceptance criteria.
- The user explicitly asks to skip planning/interview and execute immediately.
- The user asks for lightweight brainstorming only (use
planinstead). - A complete spec/plan already exists and execution should start. </Do_Not_Use_When>
<Why_This_Exists> Execution quality is usually bottlenecked by intent clarity, not just missing implementation detail. A single expansion pass often misses why the user wants a change, where the scope should stop, which tradeoffs are unacceptable, and which decisions still require user approval. This workflow applies Socratic pressure + quantitative ambiguity scoring so downstream work begins with an explicit, testable, intent-aligned spec. </Why_This_Exists>
<Depth_Profiles>
- Quick (
--quick): fast pre-spec pass; target threshold<= 0.30; max rounds 5. - Standard (
--standard, default): full requirement interview; target threshold<= 0.20; max rounds 12. - Deep (
--deep): high-rigor exploration; target threshold<= 0.15; max rounds 20.
Profile max rounds is a hard cap, not a target. Do not continue only to reach a numbered round count.
If no flag is provided, use Standard. </Depth_Profiles>
<Execution_Policy>
- Ask ONE question per round (never batch multiple interview rounds into one AskUserQuestion call).
- Ask about intent and boundaries before implementation detail.
- Target the weakest clarity dimension each round (see stage-priority rules below).
- Treat every answer as a claim to pressure-test before moving on: the next question should usually demand evidence or examples, expose a hidden assumption, force a tradeoff or boundary, or reframe root cause vs symptom.
- Do not rotate to a new clarity dimension just for coverage when the current answer is still vague; stay on the same thread until one layer deeper, one assumption clearer, or one boundary tighter.
- Before crystallizing, complete at least one explicit pressure pass that revisits an earlier answer with a deeper, assumption-focused, or tradeoff-focused follow-up.
- Gather codebase facts via repo inspection tools (Read, Grep, Glob, Bash) before asking the user about internals.
- Always run a preflight context intake before the first interview question.
- For brownfield work, preflight must include doc/context grounding before user-facing questions: inspect applicable
AGENTS.md/CLAUDE.mdfiles, README/getting-started docs, relevantdocs/contracts/plans/ADRs, and any project-local glossary/context files such asCONTEXT.mdorCONTEXT-MAP.mdwhen present. - Treat existing repo language as evidence, not authority: if the user uses a fuzzy, overloaded, or conflicting term, surface the specific doc/code wording and ask which meaning should govern.
- Cross-check user claims about current behavior against code or documented contracts when discoverable. If docs and code disagree, ask a confirmation question that names both sources.
- Use scenario-based edge-case grilling when relationships, boundaries, or handoff behavior are unclear: invent one concrete scenario that stresses the ambiguous boundary, then ask one focused question about the expected outcome.
- Durable docs, glossary, ADR, or memory updates are opt-in and public-safe only. Recommend such updates in the handoff summary, but do not automatically create public docs from interview transcripts unless the user explicitly chooses that as in-scope.
- Reduce user effort: ask only the highest-leverage unresolved question, and never ask the user for codebase facts that can be discovered directly.
- When unresolved ambiguity depends on current external best practices, invoke the
best-practice-researchskill as the bounded evidence wrapper before crystallizing requirements or handing off. - Use these transcript/spec labels:
[from-code][auto-confirmed]— exact, high-confidence codebase facts from manifests/configs or direct source evidence, with no prescription attached.[from-code]— codebase findings that are useful but inferred, pattern-based, or low/medium confidence and therefore need a confirmation-style user-facing round.[from-research]— externally sourced facts (API limits, compatibility, public docs); facts only, not decisions.[from-user]— goals, preferences, business logic, scope, non-goals, acceptance criteria, tradeoffs, and any decision-bearing interpretation.
- Treat
[from-code][auto-confirmed]and other non-user fact discoveries as context/transcript updates, not interview rounds: do not increment the user-facing round number for facts the agent can safely establish. - Auto-confirm only descriptive facts. If a finding implies what the feature should do, which pattern to follow, which tradeoff to accept, or what should stay in/out of scope, route the entire decision-bearing question to the user as
[from-user]. - Use the AskUserQuestion tool for every structured interview round. If it is unavailable, ask exactly one concise plain-text question in chat and wait for the answer.
- Re-score ambiguity after each answer and show progress transparently.
- Once ambiguity is at or below the active profile threshold, stop ordinary questioning. Run the practical closure audit: crystallize/handoff when readiness gates pass; otherwise ask only the final closure question needed to satisfy a named gate.
- Treat
max_roundsas a stop cap, not evidence that more rounds are needed. - Do not hand off to execution while ambiguity remains above threshold unless the user explicitly opts to proceed with warning.
- Do not crystallize or hand off while
Non-goalsorDecision Boundariesremain unresolved, even if the weighted ambiguity threshold is met. - Persist progress with the task list (TaskCreate/TaskUpdate) and/or append to
.workbuddy/memory/YYYY-MM-DD.md; do not rely on any persistent "mode" file. </Execution_Policy>
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.
- 10d ago First seen · 254 lines · 24 tokens per session scan A fbd733e9238e
deep-interview is a skill published in the GitHub repository mrzhangguoguo/oh-my-workbuddy (2 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 4,033 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 2026-08-31.
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