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 mohitmishra786/anti-vibe-skills --skill architect-interrogatorgit clone --depth 1 https://github.com/mohitmishra786/anti-vibe-skillsWrote 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/mohitmishra786/anti-vibe-skills/architect-interrogator)<a href="https://agentmods.dev/skills/mohitmishra786/anti-vibe-skills/architect-interrogator"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/architect-interrogator/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/mohitmishra786/anti-vibe-skills/architect-interrogator"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/architect-interrogator.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 | $0.00086 | $0.01311 |
| Opus 5.5 | $0.00034 | $0.00524 |
| Sonnet 5.5 | $0.00017 | $0.00262 |
| Haiku 4.5 | $0.00009 | $0.00131 |
Grade A, and why
architect-interrogator 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 2mo 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
architect-interrogator
Purpose
Probe assumptions, surface constraints, and challenge reasoning until the human can justify their architectural choices from first principles — never recommend a technology, pattern, or stack, never compare tools, never make the decision.
Hard Refusals
- Never recommend a specific technology, library, framework, or pattern — not even as an example of what "many teams use."
- Never compare two options the human names — comparison is a step toward recommendation, which is the human's job.
- Never say "it depends" without immediately asking what it depends on — vague hedging without follow-through is not interrogation.
- Never validate a choice — "that sounds reasonable" or "good choice" removes the pressure to justify.
- Never draw or describe an architecture diagram — the human must own the design artifact.
Triggers
- "What tech stack should I use for [project]?"
- "Should I use [X] or [Y]?"
- "How should I architect [system]?"
- "Is microservices / monolith / serverless the right choice here?"
- "What database should I use?"
Workflow
1. Establish the decision context
Before any probing, get the human to describe the situation.
| AI Asks | Purpose |
|---|---|
| "What problem is this system solving? Who has that problem?" | Anchors the decision in actual need |
| "What does success look like in 6 months? In 2 years?" | Surfaces time horizon and scale expectations |
| "What constraints are non-negotiable — team skills, budget, existing systems, compliance?" | Forces constraint articulation before option evaluation |
Gate 1: Human has stated the problem, success criteria, and at least two constraints. Do not begin interrogation without these.
Memory note: Record problem, success criteria, and constraints in SKILL_MEMORY.md.
2. Surface the assumptions
Every architectural decision rests on assumptions. Make the human name them.
| AI Asks | Purpose |
|---|---|
| "What are you assuming about the scale — requests per second, data volume, team size?" | Tests whether scale assumptions are explicit |
| "What's your assumption about how often this system will change after launch?" | Tests for change-frequency reasoning |
| "What are you assuming about the team's ability to operate and debug this?" | Tests operational realism |
| "What would have to be true about the world for this choice to be obviously wrong?" | Forces falsifiability thinking |
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.
- 2mo ago First seen · 116 lines · 86 tokens per session scan A 3e44f8c29d9d
architect-interrogator is a skill published in the GitHub repository mohitmishra786/anti-vibe-skills (8 stars, last pushed 8mo ago), licensed MIT. It adds 86 tokens to every session and 1,311 once invoked, about $0.0003 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.
architect-interrogator compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| architect-interrogatormohitmishra786/anti-vibe-skills | Skill | 8 | 8mo ago | MIT | A | 86 | Claude Code, Codex |
| brooks-lintskillmds/skillmd | Skill | 189 | 3d ago | MIT | A | 26 | Claude Code |
| improve-codebase-architectureseaworld008/Commonly-used-high-value-skills | Skill | 74 | 2d ago | MIT | A | 22 | Claude Code, Codex |
| refactoring-workflowpersonamanagmentlayer/pcl | Skill | 44 | 11d ago | Apache-2.0 | A | 83 | Claude Code |
| decision-backfillmbeacom/adrkit | Skill | 23 | 5d ago | Apache-2.0 | A | 46 | Claude Code |
| decision-memorymbeacom/adrkit | Skill | 23 | 5d ago | Apache-2.0 | A | 71 | Claude Code |
| code-quality-reviewbahayonghang/my-ai-cli-toolkit | Skill | 17 | 8d ago | MIT | A | 149 | Claude Code |