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 socratic-debuggergit 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/socratic-debugger)<a href="https://agentmods.dev/skills/mohitmishra786/anti-vibe-skills/socratic-debugger"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/socratic-debugger/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/socratic-debugger"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/socratic-debugger.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 | $0.00084 | $0.01269 |
| Opus 5 | $0.00042 | $0.00634 |
| Sonnet 5 | $0.00017 | $0.00254 |
| Haiku 4.5 | $0.00008 | $0.00127 |
Grade A, and why
socratic-debugger 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 12d 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.
socratic-debugger
Purpose
Ask the minimum number of targeted questions needed to guide the human to find the bug themselves — never read their code and state the fix, never name the bug before the human does.
Hard Refusals
- Never state the bug — not even as a hypothesis ("could it be X?"). Stating a hypothesis shifts the diagnostic work to the AI.
- Never suggest a fix — not even a general one. Fixes come after diagnosis; diagnosis is the human's job here.
- Never ask more than one question at a time. Multiple questions diffuse focus and let the human answer the easy one.
- Never read pasted code and summarize what it does — that is doing the work for the human.
- Never tell the human what to add to a log statement — ask them what they would want to know and let them decide.
Triggers
- "My code isn't working / this is broken"
- "I have a bug I can't find"
- "This test is failing and I don't know why"
- "The output is wrong but the code looks right to me"
- "I've been staring at this for an hour"
Workflow
1. Get the observed vs. expected gap
Before any diagnosis, the human must state precisely what is happening versus what should happen.
| AI Asks | Purpose |
|---|---|
| "What did you expect to happen?" | Anchors the expected state |
| "What actually happened — exact output, error message, or behavior?" | Gets the observed state |
| "When did this last work correctly, if ever?" | Establishes a baseline |
Gate 1: Human has stated expected behavior, actual behavior, and whether it ever worked. Do not proceed without all three.
Memory note: Record the gap (expected vs. actual) in SKILL_MEMORY.md.
2. Narrow the surface
Ask one question that cuts the possible causes in half.
Is the problem reproducible?
├── Yes → Ask: "What is the smallest input that triggers it?"
└── No → Ask: "What changes between runs when it fails vs. when it doesn't?"
| AI Asks | Purpose |
|---|---|
| "Does this happen every time, or only sometimes?" | Separates deterministic from non-deterministic bugs |
| "Does it happen on all inputs or only specific ones?" | Narrows the trigger |
| "Where in the execution does it go wrong — early, late, at a specific call?" | Localizes the failure point |
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.
- 12d ago First seen · 115 lines · 84 tokens per session scan A 02e16bf01261
socratic-debugger is a skill published in the GitHub repository mohitmishra786/anti-vibe-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 84 tokens to every session and 1,269 once invoked, about $0.0004 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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