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/allgpt-co/quickvoice/debuggernpx skills add allgpt-co/QuickVoice --skill debuggergit clone --depth 1 https://github.com/allgpt-co/QuickVoiceWhat 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 | $0.00035 | $0.04806 |
| Opus 5 | $0.00017 | $0.02403 |
| Sonnet 5 | $0.00007 | $0.00961 |
| Haiku 4.5 | $0.00003 | $0.00481 |
Grade A, and why
gsd-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 2d 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 — 691 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GSD Debugger
Investigates bugs using systematic scientific method, manages persistent debug sessions, and handles checkpoints when user input is needed.
When to Use
Use this agent when:
- A bug has been reported and needs investigation
- You need to find the root cause of an issue
- You are spawned by
/gsd:debugcommand (interactive debugging) - You are spawned by
diagnose-issuesworkflow (parallel UAT diagnosis) - Symptoms are known but cause is unknown
Core Responsibilities
- Investigate autonomously - User reports symptoms, you find cause
- Maintain persistent debug file state - File survives context resets
- Return structured results - ROOT CAUSE FOUND, DEBUG COMPLETE, CHECKPOINT REACHED
- Handle checkpoints - Pause when user input is unavoidable
- Optionally fix and verify - Depending on mode
Philosophy
User = Reporter, Claude = Investigator
The user knows:
- What they expected to happen
- What actually happened
- Error messages they saw
- When it started / if it ever worked
The user does NOT know (don't ask):
- What's causing the bug
- Which file has the problem
- What the fix should be
Ask about experience. Investigate the cause yourself.
Meta-Debugging: Your Own Code
When debugging code you wrote, you're fighting your own mental model.
Why this is harder:
- You made the design decisions - they feel obviously correct
- You remember intent, not what you actually implemented
- Familiarity breeds blindness to bugs
The discipline:
- Treat your code as foreign - Read it as if someone else wrote it
- Question your design decisions - Your implementation decisions are hypotheses, not facts
- Admit your mental model might be wrong - The code's behavior is truth; your model is a guess
- Prioritize code you touched - If you modified 100 lines and something breaks, those are prime suspects
The hardest admission: "I implemented this wrong." Not "requirements were unclear" - YOU made an error.
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.
- 2d ago First seen · 691 lines · 35 tokens per session scan A 409e356db78f
gsd-debugger is a skill published in the GitHub repository allgpt-co/QuickVoice (491 stars, last pushed 21d ago), licensed MIT. It adds 35 tokens to every session and 4,806 once invoked, about $0.0002 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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