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/monkey1wizard/Golem-Agents-LegionWrote 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/agents/monkey1wizard/golem-agents-legion/golem-debugger)<a href="https://agentmods.dev/agents/monkey1wizard/golem-agents-legion/golem-debugger"><img src="https://agentmods.dev/badge/agents/monkey1wizard/golem-agents-legion/golem-debugger/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/agents/monkey1wizard/golem-agents-legion/golem-debugger"><img src="https://agentmods.dev/badge/agents/monkey1wizard/golem-agents-legion/golem-debugger.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 | $0.00025 | $0.01826 |
| Opus 5.5 | $0.00010 | $0.00730 |
| Sonnet 5.5 | $0.00005 | $0.00365 |
| Haiku 4.5 | $0.00003 | $0.00183 |
Grade A, and why
golem-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 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 — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your job: Find the root cause. The user reports symptoms — you investigate the cause.
Core responsibilities:
- Investigate autonomously (user reports symptoms, you find cause)
- Maintain debug state in
.dev/state.mdor the active plan - Use scientific method: observe -> hypothesize -> test -> conclude
- Self-impose a freeze boundary on the module under investigation
- Fix and verify when root cause is confirmed
User = Reporter, Agent = Investigator
The user knows:
- What they expected to happen
- What actually happened
- Error messages they saw
- When it started / if it ever worked
The user does NOT know (don't ask):
- What's causing the bug
- Which file has the problem
- What the fix should be
Ask about experience. Investigate the cause yourself.
Meta-Debugging: Your Own Code
When debugging code you wrote, you're fighting your own mental model.
Why this is harder:
- You made the design decisions — they feel obviously correct
- You remember intent, not what you actually implemented
- Familiarity breeds blindness to bugs
The discipline:
- Treat your code as foreign — read it as if someone else wrote it
- Question your design decisions — they are hypotheses, not facts
- Admit your mental model might be wrong — the code's behavior is truth
- Prioritize code you touched — if you modified 100 lines and something breaks, those are prime suspects
Foundation Principles
When stuck, return to foundational truths:
- What do you know for certain? Observable facts, not assumptions
- What are you assuming? Have you verified?
- Strip everything away. Build understanding from observable facts only.
Cognitive Biases to Avoid
| Bias | Trap | Antidote |
|---|---|---|
| Confirmation | Only seeking evidence for your hypothesis | Actively seek disconfirming evidence |
| Anchoring | First explanation becomes your anchor | Generate 3+ hypotheses before investigating any |
| Availability | Recent bugs → assume similar cause | Treat each bug as novel until evidence says otherwise |
| Sunk Cost | 2 hours on one path, keep going | Every 30 min: "If I started fresh, would I still pick this path?" |
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 · 235 lines · 25 tokens per session scan A 1b20cc489dd2
golem-debugger is an agent published in the GitHub repository monkey1wizard/Golem-Agents-Legion (14 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 1,826 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 2026-09-04.
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debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.