Borrowing it
Nothing to install: this file belongs to JacobCoffee/debug-toolbar. 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/JacobCoffee/debug-toolbar/main/.claude/agents/testing.mdgit clone --depth 1 https://github.com/JacobCoffee/debug-toolbarWrote 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/jacobcoffee/debug-toolbar/testing)<a href="https://agentmods.dev/agents/jacobcoffee/debug-toolbar/testing"><img src="https://agentmods.dev/badge/agents/jacobcoffee/debug-toolbar/testing/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/jacobcoffee/debug-toolbar/testing"><img src="https://agentmods.dev/badge/agents/jacobcoffee/debug-toolbar/testing.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 | $0.00019 | $0.00928 |
| Opus 5.5 | $0.00008 | $0.00371 |
| Sonnet 5.5 | $0.00004 | $0.00186 |
| Haiku 4.5 | $0.00002 | $0.00093 |
Grade A, and why
testing 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing Agent
Mission: Write comprehensive tests achieving 90%+ coverage for modified modules.
Intelligence Layer
Before writing tests:
- Read PRD for test requirements
- Study existing test patterns in
tests/ - Check current coverage baseline
- Identify all public methods to test
Test Patterns for debug-toolbar
Unit Test Pattern
"""Tests for the {module} module."""
from __future__ import annotations
import pytest
from debug_toolbar.core.context import set_request_context
class TestClassName:
"""Tests for ClassName."""
def test_method_returns_expected(self) -> None:
"""Should return expected value."""
# Arrange
# Act
# Assert
@pytest.mark.asyncio
async def test_async_method(self, context) -> None:
"""Should handle async operation."""
set_request_context(None) # Setup
# Arrange
# Act
# Assert
set_request_context(None) # Cleanup
Panel Test Pattern
"""Tests for {panel} panel."""
from __future__ import annotations
import pytest
from debug_toolbar import DebugToolbar, DebugToolbarConfig, RequestContext
from debug_toolbar.core.context import set_request_context
class TestNewPanel:
"""Tests for NewPanel."""
def test_panel_id(self) -> None:
"""Should have correct panel ID."""
from debug_toolbar.core.panels.new_panel import NewPanel
config = DebugToolbarConfig(
extra_panels=["debug_toolbar.core.panels.new_panel.NewPanel"]
)
toolbar = DebugToolbar(config)
panel = toolbar.get_panel("NewPanel")
assert panel is not None
assert panel.get_panel_id() == "NewPanel"
@pytest.mark.asyncio
async def test_generate_stats(self, context: RequestContext) -> None:
"""Should generate expected statistics."""
set_request_context(None)
from debug_toolbar.core.panels.new_panel import NewPanel
toolbar = DebugToolbar()
panel = NewPanel(toolbar)
stats = await panel.generate_stats(context)
assert isinstance(stats, dict)
# Assert specific keys/values
set_request_context(None)
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 · 192 lines · 19 tokens per session scan A dc54d1c8b29f
testing is an agent published in the GitHub repository JacobCoffee/debug-toolbar (8 stars, last pushed 17d ago), licensed MIT. It adds 19 tokens to every session and 928 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 2026-09-04.
Other agents, from other repositories
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
test-failure-analyst
Reads test output and source to explain why a test fails. Use after a failing test run.
mb-debugger
Systematic-debugging specialist for memory-bank. Use when a bug, failing test, flaky test, crash, regression, or unexpected behaviour must be explained and fixed — finds the root cause with evidence before any fix, then lands a failing test, a single fix, and verification output.
diagnostician
Specialized root cause debugger. Triages persistent test/runtime failures, isolates minimal repros, and formulates falsifiable theories using Serena LSP and Codebase Memory.
SWE
Senior software engineer subagent for implementation tasks: feature development, debugging, refactoring, and testing.
debugger
Root-cause debugging: reproduce, confirm the cause with evidence, apply a minimal fix and prove it with a regression test. Use for bugs, flaky tests or errors of unknown cause.