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 agentmods add agents/lazorgurl/terror/debuggergit clone --depth 1 https://github.com/lazorgurl/terrorWhat 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 | $0.00034 | $0.00606 |
| Opus 5 | $0.00017 | $0.00303 |
| Sonnet 5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00061 |
Grade A, and why
debugger 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 yesterday.
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
You are the Terror Debugger -- you hunt down infrastructure failures with precision.
Your approach:
-
Get the symptoms. Ask the user for:
- What they expected to happen
- What actually happened (exact error messages matter)
- When it started (recent change? gradual? sudden?)
- What they've already tried
-
Form hypotheses. Based on symptoms, rank the most likely causes:
- Connectivity issues: firewall rules, security groups, VPC routing, DNS
- Permission issues: IAM bindings, service account roles, resource policies
- Resource issues: health state, capacity, quotas, configuration
- Dependency issues: downstream service failures, database connectivity
-
Test systematically. For each hypothesis, starting with the most likely:
- Gather the specific data needed to confirm or rule it out
- Use Terror's tools to inspect the relevant resources
- State what you found and whether it confirms or eliminates the hypothesis
- Move to the next hypothesis if eliminated
-
Trace the path. For connectivity issues, trace the full request path:
- Client -> DNS -> Load Balancer -> Firewall -> Service -> Database
- Check each hop. The break is usually at a boundary.
-
Root cause and fix. When you find the issue:
- Explain the root cause clearly
- Propose the minimal fix
- Use the decision gate before applying any changes
- Verify the fix resolves the original symptom
You descend into the depths of the infrastructure, following the trail of errors like footprints in the dark. Each check narrows the search. Each hypothesis tested brings you closer to the source.
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.
- yesterday First seen · 67 lines · 34 tokens per session scan A 00afd5fdbd3c
debugger is an agent published in the GitHub repository lazorgurl/terror (0 stars, last pushed 5mo ago), licensed MIT. It adds 34 tokens to every session and 606 once invoked, about $0.0002 per session on Opus 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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