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/latestaiagents/agent-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/commands/latestaiagents/agent-skills/debug-agent)<a href="https://agentmods.dev/commands/latestaiagents/agent-skills/debug-agent"><img src="https://agentmods.dev/badge/commands/latestaiagents/agent-skills/debug-agent/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/commands/latestaiagents/agent-skills/debug-agent"><img src="https://agentmods.dev/badge/commands/latestaiagents/agent-skills/debug-agent.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 | $0.00008 | $0.00348 |
| Opus 5.5 | $0.00003 | $0.00139 |
| Sonnet 5.5 | $0.00002 | $0.00070 |
| Haiku 4.5 | $0.00001 | $0.00035 |
Grade A, and why
debug-agent 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
/debug-agent
Diagnose and fix issues in your multi-agent system.
What I Need
Tell me:
- What's the unexpected behavior?
- Which agent(s) are involved?
- Do you have traces/logs?
- Is it reproducible?
Debug Process
Step 1: Identify Failure Point
I'll help locate:
- Which agent failed
- At what step in the workflow
- What was the input/output
Step 2: Analyze Root Cause
Common issues:
- Prompt ambiguity
- Tool execution failures
- State corruption
- Infinite loops
- Token limit exceeded
Step 3: Trace Analysis
If using LangSmith:
from langsmith import Client
client = Client()
runs = client.list_runs(project_name="your-project", error=True)
Step 4: Fix & Verify
I'll provide:
- Specific fix for the issue
- Test case to verify
- Prevention measures
Common Issues
| Symptom | Likely Cause | Fix |
|---|---|---|
| Agent loops forever | No exit condition | Add max_iterations |
| Wrong agent selected | Poor routing | Improve router prompt |
| State lost | Missing checkpointer | Add persistence |
| Timeout | Agent stuck | Add timeout + fallback |
| Inconsistent results | Non-deterministic | Set temperature=0 |
Debug Checklist
[ ] Check agent prompts for ambiguity
[ ] Verify tool definitions are correct
[ ] Inspect state at each transition
[ ] Review routing logic
[ ] Check for token limits
[ ] Verify checkpointing works
[ ] Test edge cases
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 · 68 lines · 8 tokens per session scan A 7f90d74322bf
debug-agent is a command published in the GitHub repository latestaiagents/agent-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 8 tokens to every session and 348 once invoked, about $0.0000 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.
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