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/orinks/accessiweather/deep-interviewnpx skills add Orinks/AccessiWeather --skill deep-interviewgit clone --depth 1 https://github.com/Orinks/AccessiWeatherWhat 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 | $0.00019 | $0.06391 |
| Opus 5 | $0.00010 | $0.03195 |
| Sonnet 5 | $0.00004 | $0.01278 |
| Haiku 4.5 | $0.00002 | $0.00639 |
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 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 — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<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
ralplan,autopilot,ralph, orteam</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 PRD/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 orchestration modes begin with an explicit, testable, intent-aligned spec. </Why_This_Exists>
<Depth_Profiles>
- Quick (
--quick): fast pre-PRD 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 - Autoresearch (
--autoresearch): same interview rigor as Standard, but specialized for$autoresearchmission readiness and.omx/specs/artifact handoff
If no flag is provided, use Standard.
<Mode_Flags>
--autoresearch: switch the interview into autoresearch-intake mode for$autoresearchhandoff. In this mode, the interview should converge on a validator-ready research mission, write canonical artifacts under.omx/specs/, and preserve the explicitrefine furthervslaunchboundary for downstream skill intake. </Mode_Flags> </Depth_Profiles>
<Execution_Policy>
- Ask ONE question per round (never batch multiple interview rounds into one
questions[]form) - Ask about intent and boundaries before implementation detail
- Target the weakest clarity dimension each round after applying the 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
explorebefore asking user about internals - When session guidance enables
USE_OMX_EXPLORE_CMD, preferomx explorefor simple read-only brownfield fact gathering; keep prompts narrow and concrete, and keep ambiguous or non-shell-only investigation on the richer normal path and fall back normally ifomx exploreis unavailable. - Always run a preflight context intake before the first interview question
- If initial context is oversized or would exceed the prompt budget, do not paste or forward the raw payload into interview prompts; request and record a prompt-safe initial-context summary first
- The oversized initial-context summary gate is blocking: wait for the concise summary before ambiguity scoring, crystallizing artifacts, or any downstream execution handoff
- The summary must preserve goals, constraints, success criteria, non-goals, decision boundaries, and references to any full source documents so downstream consumers receive a prompt-safe but faithful context
- Keep total prompt payloads within a safe budget by summarizing or trimming retained history; preserve newest/highest-signal answers and never let raw oversized context crowd out the current question
- Reduce user effort: ask only the highest-leverage unresolved question, and never ask the user for codebase facts that can be discovered directly
- For brownfield work, prefer evidence-backed confirmation questions such as "I found X in Y. Should this change follow that pattern?"
- In attached-tmux Codex CLI, deep-interview uses
omx questionas the required OMX-owned structured questioning path for every interview round - When invoking
omx questionthrough attached-tmux Bash/tool paths, preserve the leader-pane return target by prefixing the command withOMX_QUESTION_RETURN_PANE=$TMUX_PANE(or a concrete%panevalue) - If you launch
omx questionin a background terminal, immediately wait for that background terminal to finish and read its JSON answer before scoring ambiguity, asking another round, or handing off - Treat
answers[]as the primaryomx questionsuccess contract. For a single interview round, readanswers[0].answer; use legacy top-levelansweronly as a compatibility fallback when needed. - If the current runtime is outside tmux and cannot render
omx question, use the native structured question tool when available; otherwise ask exactly one concise plain-text question and wait for the answer - Re-score ambiguity after each answer and show progress transparently
- Do not hand off to execution while ambiguity remains above threshold unless 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 - Treat early exit as a safety valve, not the default success path
- Persist mode state for resume safety (
state_write/state_read) </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.
- 3d ago First seen · 469 lines · 19 tokens per session scan A b047982412bd
deep-interview is a skill published in the GitHub repository Orinks/AccessiWeather (24 stars, last pushed 9d ago), licensed MIT. It adds 19 tokens to every session and 6,391 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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