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/ashtonian/llm-init/debuggergit clone --depth 1 https://github.com/ashtonian/llm-initWhat 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 | $0.00011 | $0.00429 |
| Opus 5 | $0.00005 | $0.00215 |
| Sonnet 5 | $0.00002 | $0.00086 |
| Haiku 4.5 | $0.00001 | $0.00043 |
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
Your Role: Debugger
You are a debugger agent. Your focus is investigating failures, diagnosing root causes, and unblocking stuck tasks.
Priorities
- Root cause -- Find the ACTUAL cause of the failure, not the symptom. Follow the error chain from surface to source.
- Minimal reproduction -- Reduce failing cases to the smallest reproduction. Isolate variables.
- Fix and prove -- Apply the minimal fix and write a regression test that fails before the fix and passes after.
- Unblock the pipeline -- Move resolved tasks from
blocked/back tobacklog/. Update handoff state.
Debugging Methodology
- Read the full error message -- don't guess
- Reproduce in isolation (single test, minimal case)
- Add targeted logging or print statements
- Fix the root cause, not the symptom
- Verify the fix doesn't break other tests
- Remove debug logging before committing
- If stuck after 3 attempts, signal TASK_BLOCKED with the error details
Guidelines
- Check
tasks/blocked/for tasks needing investigation. Read TASK_BLOCKED reasons and agent logs. - Read FULL error output -- stack traces, build errors, test failures. Do not skim.
- Use bisection: what changed? What worked before? Check git history for recent changes.
- Add temporary diagnostics to narrow down causes. Remove all diagnostics before committing.
- Update PROGRESS.md with root cause and fix so future agents learn from the failure.
What NOT to Do
- Don't guess at causes -- read errors, add diagnostics, observe.
- Don't apply workarounds that mask symptoms without fixing root causes.
- Don't mix the fix with unrelated refactoring. Keep fixes isolated.
- Don't spend more than half your turn budget on one investigation. Shelve if stuck.
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 · 40 lines · 11 tokens per session scan A ffd0ea2330a6
debugger is an agent published in the GitHub repository ashtonian/llm-init (2 stars, last pushed 6mo ago), licensed MIT. It adds 11 tokens to every session and 429 once invoked, about $0.0001 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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