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 yeaight7/agent-powerups --skill systematic-debugginggit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/systematic-debugging)<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/systematic-debugging"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/systematic-debugging/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/yeaight7/agent-powerups/systematic-debugging"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/systematic-debugging.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 | $0.00022 | $0.01453 |
| Opus 5.5 | $0.00009 | $0.00581 |
| Sonnet 5.5 | $0.00004 | $0.00291 |
| Haiku 4.5 | $0.00002 | $0.00145 |
Grade A, and why
systematic-debugging 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Find the root cause of any bug before attempting a fix. Random fixes waste time and create new bugs. Symptom fixes are failure.
Core principle: ALWAYS find root cause before attempting fixes.
When to Use
Use for ANY technical issue:
- Test failures
- Bugs in production
- Unexpected behavior
- Performance problems
- Build failures
- Integration issues
Use this especially when:
- Under time pressure (emergencies make guessing tempting)
- "Just one quick fix" seems obvious
- You've already tried multiple fixes
- Previous fix didn't work
- You don't fully understand the issue
Do not skip when:
- Issue seems simple (simple bugs have root causes too)
- You're in a hurry (rushing guarantees rework)
- Someone wants it fixed immediately (systematic is faster than thrashing)
Inputs
- Bug description or error message.
- Stack trace or reproduction steps.
- Environment context (OS, versions, recent changes).
- Access to the codebase and test suite.
Workflow
You MUST complete each phase before proceeding to the next.
Phase 1: Root Cause Investigation
Before attempting ANY fix:
-
Read error messages carefully — Don't skip past errors or warnings. Read stack traces completely. Note line numbers, file paths, error codes.
-
Reproduce consistently — Can you trigger it reliably? What are the exact steps? If not reproducible: gather more data, don't guess.
-
Check recent changes — What changed that could cause this? Git diff, recent commits, new dependencies, config changes, environmental differences.
-
Gather evidence in multi-component systems — When the system has multiple components (CI → build → signing, API → service → database):
For EACH component boundary: - Log what data enters the component - Log what data exits the component - Verify environment/config propagation - Check state at each layer Run once to gather evidence showing WHERE it breaks. Then analyze to identify the failing component. Then investigate that specific component.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 156 lines · 22 tokens per session scan A ed7795a18f7a
systematic-debugging is a skill published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 19d ago), licensed Apache-2.0. It adds 22 tokens to every session and 1,453 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 2026-09-14.
Other skills, from other repositories
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.
simplify-code
Sequential 3-lens cleanup of recent code changes.
node-inspect-debugger
Debug Node.js via --inspect + Chrome DevTools Protocol.
python-debugpy
Debug Python: pdb REPL + debugpy remote (DAP).
hqe
Comprehensive codebase health auditing, remediation, and verification skill based on the canonical HQE Protocol v5.0.0.
adk-debug
Diagnoses misbehaving ADK agents by inspecting sessions, events, tool calls, and the exact request that reached the model. Covers the adk run CLI and the adk web dev server with its session, trace, and debug HTTP endpoints. Use when an agent returns the wrong answer, ignores a tool or swallows a tool error, hangs…