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 OXI-717/ai-native-toolkit --skill deep-interviewgit clone --depth 1 https://github.com/OXI-717/ai-native-toolkitWrote 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/oxi-717/ai-native-toolkit/deep-interview)<a href="https://agentmods.dev/skills/oxi-717/ai-native-toolkit/deep-interview"><img src="https://agentmods.dev/badge/skills/oxi-717/ai-native-toolkit/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/oxi-717/ai-native-toolkit/deep-interview"><img src="https://agentmods.dev/badge/skills/oxi-717/ai-native-toolkit/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 | $0.00029 | $0.01223 |
| Opus 5.5 | $0.00012 | $0.00489 |
| Sonnet 5.5 | $0.00006 | $0.00245 |
| Haiku 4.5 | $0.00003 | $0.00122 |
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.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Interview — Task Clarification
Clarify a vague task through focused one-at-a-time questions, then produce a structured brief.
Input: $ARGUMENTS
When to use
- Task is too vague for brainstorming ("make it better", "fix the architecture", "add notifications")
- Scope is unclear — could be 1 hour or 1 week
- Multiple interpretations possible
- User hasn't thought through non-goals or constraints yet
When NOT to use
- Task is already clear (specific file, specific bug, specific feature)
- User provided a spec or detailed description
- Already in brainstorming/planning phase
Process
Phase 1: Context Scan (silent, no output to user)
Before asking any questions:
- For the project root and every directory scoped to the task, discover and read each applicable
AGENTS.md; where a scope has noAGENTS.md, read itsCLAUDE.mdfallback. Recursively read the relative files referenced by@imports in each manifest or imported rule before proceeding. - Check git log for recent work context (last 10 commits)
- Scan project structure (top-level dirs, key config files)
- If task mentions specific areas — read those files
This gives you context to ask informed questions, not generic ones.
Phase 2: Interview (interactive)
RULES:
- Ask ONE question at a time. Never dump multiple questions.
- Wait for answer before asking next question.
- Questions must be specific and actionable, not philosophical.
- Use context from Phase 1 to ask informed questions (reference files, patterns, existing code).
- Skip questions whose answers are obvious from the codebase.
- Maximum 7 questions total. Stop earlier if picture is clear.
- After each answer, briefly acknowledge and move to next question.
Question flow (adapt order based on responses, skip what's already clear):
1. Intent
"What's the end result you want? Not how — what should be different when this is done?"
2. Trigger
"What prompted this? A bug, a user request, technical debt, new requirement?"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed · -5 lines · -46 tokens per session b8fd4d7ba010
- 1mo ago First seen · 171 lines · 75 tokens per session scan A 87829457e135
deep-interview is a skill published in the GitHub repository OXI-717/ai-native-toolkit (9 stars, last pushed 21d ago), licensed MIT. It adds 29 tokens to every session and 1,223 once invoked, about $0.0001 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.
Other skills, from other repositories
code-changes
Workflow for any task that ends in code changes: issue analysis or triage, pull request review comments, features, bug fixes, refactors. Invoke at the start of such a task, before reading or writing code.
spec-to-code-compliance
Verifies code implements exactly what documentation specifies for blockchain audits. Use when comparing code against whitepapers, finding gaps between specs and implementation, or performing compliance checks for protocol implementations.
etherscan-contract-review
Review and explain verified deployed EVM smart contracts from a contract address and chain. Use when a user asks to break down what a Solidity contract does, map its architecture and source files, identify user/admin flows, proxy or implementation roles, asset movement, privileged controls, events, state variables, or…
fork-choice-audit
L1 trigger - audits fork-choice rule implementation (LMD-GHOST, Tendermint locking, Nakamoto longest-chain) for equivocation handling, slot-vs-block reasoning, duplicate block handling, and chain reorg correctness.
triage-nda
Ten-minute NDA triage — classifies an incoming NDA as GREEN (sign under standard delegation), YELLOW (targeted fixes, listed), or RED (full review). Screens mutuality, term and survival, definition breadth, embedded non-solicits or non-competes, missing standard carve-outs, residuals clauses, and IP assignment…
design-reviewer
Use after AC and before RED for any wave that ships UI. Performs component API audit against installed dist files, produces per-route mockup, defines visual ACs, flags design-system gaps. Output written to .wave/dr.md.