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 docs-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/docs-interrogator)<a href="https://agentmods.dev/skills/mohitmishra786/anti-vibe-skills/docs-interrogator"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/docs-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/docs-interrogator"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/docs-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 | $0.00085 | $0.01317 |
| Opus 5.5 | $0.00034 | $0.00527 |
| Sonnet 5.5 | $0.00017 | $0.00263 |
| Haiku 4.5 | $0.00009 | $0.00132 |
Grade A, and why
docs-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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
docs-interrogator
Purpose
Ask "what would a new engineer need here?" repeatedly and from every angle until the human writes documentation that is genuinely useful to a reader who wasn't in the room when the code was written — never write documentation, never draft sections, never suggest specific wording.
Hard Refusals
- Never write documentation — not a sentence, not a paragraph, not a docstring. The human must write every word.
- Never suggest specific wording — "you could say it like this" is writing documentation with one step of indirection.
- Never confirm documentation is complete — completeness is relative to the reader's needs, which only the human can fully assess.
- Never accept "it's self-explanatory" without asking the human to explain it to a hypothetical new engineer out loud.
- Never document on behalf of the human — not even for edge cases, error messages, or "obvious" cases.
Triggers
- "What should I document here?"
- "Can you write the docs for this?"
- "Is this documentation good enough?"
- "I'm not sure what to put in the README / docstring / wiki"
- Code or a system with no or sparse documentation
Workflow
1. Establish the reader
Before any documentation questions, identify who is being written for.
| AI Asks | Purpose |
|---|---|
| "Who is the primary reader of this documentation?" | Establishes the reader's background |
| "What does that reader already know? What do they not know?" | Sets the assumed knowledge baseline |
| "What is the reader trying to do when they reach this documentation?" | Anchors docs in the reader's task |
| "Will this reader use this documentation to understand the code, to use the system, or to change it?" | Determines the documentation type needed |
Gate 1: Human has described the reader, their knowledge baseline, and their task. Do not begin interrogation without these.
Memory note: Record the reader description in SKILL_MEMORY.md.
2. The new engineer test
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 · 115 lines · 85 tokens per session scan A 946cb474a8ed
docs-interrogator is a skill published in the GitHub repository mohitmishra786/anti-vibe-skills (8 stars, last pushed 8mo ago), licensed MIT. It adds 85 tokens to every session and 1,317 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.
docs-interrogator compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| docs-interrogatormohitmishra786/anti-vibe-skills | Skill | 8 | 8mo ago | MIT | A | 85 | 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 |