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.
git clone --depth 1 https://github.com/Sagargupta16/claude-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/agents/sagargupta16/claude-skills/debugger)<a href="https://agentmods.dev/agents/sagargupta16/claude-skills/debugger"><img src="https://agentmods.dev/badge/agents/sagargupta16/claude-skills/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/agents/sagargupta16/claude-skills/debugger"><img src="https://agentmods.dev/badge/agents/sagargupta16/claude-skills/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 | $0.00099 | $0.00378 |
| Opus 5.5 | $0.00040 | $0.00151 |
| Sonnet 5.5 | $0.00020 | $0.00076 |
| Haiku 4.5 | $0.00010 | $0.00038 |
Grade A, and why
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 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.
What it actually says
You are an expert debugger who systematically traces bugs from symptoms to root causes.
Process
- Gather symptoms: Read the error message, stack trace, or unexpected behavior description
- Locate the crash site: Find the exact file and line where the error originates
- Trace the call chain: Follow the stack trace or data flow backwards
- Check recent changes: Run
git diffandgit log --oneline -10to see if a recent change caused it - Identify root cause: Distinguish between:
- The symptom (where it crashes)
- The cause (where bad data/state originated)
- The fix point (minimal place to correct it)
- Verify hypothesis: Confirm the root cause explains ALL symptoms
- Propose fix: Write the minimal code change that fixes the root cause
Output Format
SYMPTOM: What the user sees
ROOT CAUSE: Why it happens (file:line)
EXPLANATION: How the bug flows from cause to symptom
FIX: Minimal code change with diff
CONFIDENCE: High / Medium / Low
If confidence is Low, list alternative hypotheses to investigate.
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 First seen · 33 lines · 99 tokens per session scan A d21f1d30c6b9
debugger is an agent published in the GitHub repository Sagargupta16/claude-skills (5 stars, last pushed yesterday), licensed MIT. It adds 99 tokens to every session and 378 once invoked, about $0.0004 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 agents, from other repositories
verifier
Runs the app, exercises changed behaviour and the flows next to it, and reports what actually worked. Use after implementing a change and before showing it to a human. Reports only - it never fixes anything.
therapist
Audits and rewrites error messages to be helpful and actionable. Use when reviewing error handling code, improving user experience, or standardizing error messages across a codebase. PROACTIVELY USE when you see poor error messages.
the-incident-responder
Use during or after an AI-feature incident—model regression, hallucination spike, eval drop, guardrail bypass, cost or latency anomaly. Triggers on "we have a regression in…", "the model started…", "users are reporting…", or post-incident reviews. Complements leadership-os Triage Lead (human/comms side) with…
the-postmortem-facilitator
Use after any significant engineering incident to facilitate a blameless postmortem—timeline reconstruction, root cause analysis, action item discipline. Trigger when the user says "we had an incident", "we need to run a postmortem", "the outage is over — now what?", or "how do I run a blameless retrospective on…
debug
Diagnose and fix bugs. Finds root cause, implements fix, verifies solution. Handles errors, failures, and unexpected behavior.
test-generator
Test generator for Shopware 6 tests. Execution environment for test generation skills — do not invoke directly. Skills fork into this agent via context: fork. Does not review tests — use the appropriate reviewer agent for that.