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 AvinashP/AgentsAtlas --skill debugginggit clone --depth 1 https://github.com/AvinashP/AgentsAtlasWrote 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/avinashp/agentsatlas/debugging)<a href="https://agentmods.dev/skills/avinashp/agentsatlas/debugging"><img src="https://agentmods.dev/badge/skills/avinashp/agentsatlas/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/avinashp/agentsatlas/debugging"><img src="https://agentmods.dev/badge/skills/avinashp/agentsatlas/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 | $0.00028 | $0.01490 |
| Opus 5.5 | $0.00011 | $0.00596 |
| Sonnet 5.5 | $0.00006 | $0.00298 |
| Haiku 4.5 | $0.00003 | $0.00149 |
Grade A, and why
debugging scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| `CORS error` | Backend config | Check Network tab, test with curl | How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
Diagnose and fix errors using scientific method with disciplined root cause analysis.
The Iron Law
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
If you haven't completed Phase 1, you cannot propose fixes. Symptom fixes are failure.
When to Use
Use for ANY technical issue:
- Test failures
- Bugs in production
- Unexpected behavior
- "It doesn't work" problems
- Build/compilation failures
- Performance problems
Use 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
Don't skip when:
- Issue seems simple (simple bugs have root causes too)
- You're in a hurry (systematic is faster than thrashing)
The Four Phases
Complete each phase before proceeding to the next.
Phase 1: Root Cause Investigation
BEFORE attempting ANY fix:
1. Read Error Messages Carefully
- Don't skip past errors or warnings
- They often contain the exact solution
- Read stack traces completely
- Note line numbers, file paths, error codes
2. Reproduce Consistently
- Can you trigger it reliably?
- What are the exact steps?
- Does it happen every time?
- If not reproducible → gather more data, don't guess
3. Check Recent Changes
- What changed that could cause this?
git diff, recent commits- New dependencies, config changes
- Environmental differences
4. Trace Data Flow
When error is deep in call stack:
- Where does the bad value originate?
- What called this with the bad value?
- Keep tracing up until you find the source
- Fix at source, not at symptom
See root-cause-tracing.md for the complete backward tracing technique.
5. Gather Evidence in Multi-Component Systems
When system has multiple components (API → service → database):
For EACH component boundary:
- Log what data enters component
- Log what data exits component
- Verify environment/config propagation
Run once to gather evidence showing WHERE it breaks
THEN analyze evidence to identify failing component
THEN investigate that specific component
What ships with it
3 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 · 186 lines · 28 tokens per session scan A da3f100e55e1
debugging is a skill published in the GitHub repository AvinashP/AgentsAtlas (7 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 1,490 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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