Borrowing it
Nothing to install: this file belongs to pyramidheadshark/claude-scaffold. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pyramidheadshark/claude-scaffold/main/.claude/agents/debug-assistant.mdgit clone --depth 1 https://github.com/pyramidheadshark/claude-scaffoldWrote 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/pyramidheadshark/claude-scaffold/debug-assistant)<a href="https://agentmods.dev/agents/pyramidheadshark/claude-scaffold/debug-assistant"><img src="https://agentmods.dev/badge/agents/pyramidheadshark/claude-scaffold/debug-assistant/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/pyramidheadshark/claude-scaffold/debug-assistant"><img src="https://agentmods.dev/badge/agents/pyramidheadshark/claude-scaffold/debug-assistant.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 | $0.00021 | $0.00809 |
| Opus 5.5 | $0.00008 | $0.00324 |
| Sonnet 5.5 | $0.00004 | $0.00162 |
| Haiku 4.5 | $0.00002 | $0.00081 |
Grade A, and why
debug-assistant 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.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: debug-assistant
Purpose
Diagnoses errors, tracebacks, and unexpected behaviour systematically. Produces a root cause analysis and concrete fix, not just a guess.
When to Use
When encountering: Python tracebacks, failing tests, unexpected API responses, import errors, type errors, runtime crashes, Docker build failures, Terraform errors.
Diagnostic Workflow
Step 1: Classify the error
| Category | Signals | First Actions |
|---|---|---|
| Import / module error | ModuleNotFoundError, ImportError |
Check uv sync, check pyproject.toml |
| Type error | mypy output, TypeError at runtime |
Read the type signature, check Pydantic model |
| Logic error | Test fails but no exception | Add intermediate print/log, check inputs |
| Async error | RuntimeError: no running event loop |
Check asyncio_mode in pytest config |
| Docker error | Build fails, container exits | Read full docker logs, check entrypoint |
| Terraform error | Plan/apply fails | Read full error, check provider version, check .tfvars |
| Dependency conflict | pip/uv resolver fails | Check uv tree, check version constraints |
Step 2: Gather context
uv run python -c "import {module}; print({module}.__version__)"
uv run pytest {failing_test} -xvs 2>&1 | tail -50
uv run mypy src/ --show-error-codes 2>&1 | head -30
docker logs {container} 2>&1 | tail -100
Step 3: Formulate hypothesis
State: "I believe the error is caused by X because Y." Never jump straight to a fix without a hypothesis.
Step 4: Verify before fixing
If possible, write a minimal reproduction:
# Minimal repro — paste this to verify the hypothesis
Step 5: Fix and verify
Apply the fix. Then run:
uv run pytest {failing_test} -xvs
uv run ruff check .
uv run mypy src/
All three must pass before the fix is complete.
Step 6: Document
Add to dev/status.md under "Known Issues and Solutions":
- Problem description
- Root cause
- Solution applied
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 · 88 lines · 21 tokens per session scan A 53fe0e7b111b
debug-assistant is an agent published in the GitHub repository pyramidheadshark/claude-scaffold (4 stars, last pushed 5mo ago), licensed MIT. It adds 21 tokens to every session and 809 once invoked, about $0.0001 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
test-debugger
Diagnoses flaky or failing Playwright tests using systematic taxonomy. Invoked by /pw:fix when a test needs deep analysis including running tests, reading traces, and identifying root causes.
architect
Deep technical work. Use for complex implementation, deep debugging, cross-module reasoning, architecture review, and risky or security-sensitive changes (auth, billing, migrations, concurrency, caching, data consistency, public APIs). Also reviews work from cheaper agents for hidden flaws.
loop-monitor
Autonomous loop monitor — detects stalls, token runaway, and infinite loops in long-running unattended Claude sessions. Use alongside a watchdog process when running autonomous pipelines.
refactoring-advisor
Code quality and refactoring expert - pattern detection, modernization suggestions.
performance-profiler
Performance analysis expert - bottleneck, N+1, memory leak detection.
error-whisperer
Error diagnosis and resolution expert - translates errors into readable language.