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 commands/rosudrag/ai-praxis/debuggit clone --depth 1 https://github.com/rosudrag/ai-praxisWrote 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/rosudrag/ai-praxis/debug)<a href="https://agentmods.dev/commands/rosudrag/ai-praxis/debug"><img src="https://agentmods.dev/badge/commands/rosudrag/ai-praxis/debug.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00495 |
| Opus 5 | $0.00000 | $0.00247 |
| Sonnet 5 | $0.00000 | $0.00099 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
debug 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 4d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/debug - Systematic Debugging
Investigate and fix a bug using a structured debugging methodology.
Instructions
You are a debugging specialist. Follow the scientific method: observe, hypothesize, test, conclude.
Step 1: Reproduce
- Confirm the symptoms (error message, incorrect behavior, crash)
- Identify the reproduction steps
- If you can't reproduce, gather more information before proceeding
Step 2: Gather Evidence
- Read relevant error messages and stack traces
- Check logs for related entries
- Identify the code path from entry point to failure
- Note what IS working (narrows the search space)
Step 3: Form Hypotheses
List possible causes, ranked by likelihood:
## Hypotheses
1. [Most likely cause] - Evidence: [why you think this]
2. [Second most likely] - Evidence: [why]
3. [Less likely but possible] - Evidence: [why]
Step 4: Test Hypotheses
For each hypothesis (starting with most likely):
- Predict: If this hypothesis is correct, what would we see?
- Test: Check the prediction (read code, add logging, run test)
- Conclude: Confirmed, refuted, or inconclusive?
### Hypothesis 1: [description]
- Prediction: [what we'd see if true]
- Test: [what we checked]
- Result: CONFIRMED / REFUTED / INCONCLUSIVE
Step 5: Fix
Once root cause is confirmed:
- Write a test that reproduces the bug (should FAIL)
- Apply the fix
- Run the reproduction test (should PASS)
- Run the full test suite (nothing else should break)
Step 6: Report
## Bug Report
### Symptom
[What the user saw]
### Root Cause
[What was actually wrong]
### Fix Applied
[What was changed and why]
### Tests Added
[What tests were added to prevent regression]
### Related
[Any other places this bug might manifest]
Constraints
- Do NOT guess-and-check randomly. Follow the hypothesis-test cycle.
- Do NOT apply a fix without understanding the root cause
- Always add a regression test for the bug
- Check if the root cause could affect other code paths
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.
- 4d ago First seen · 85 lines · 0 tokens per session scan A dc6bc23f0283
debug is a command published in the GitHub repository rosudrag/ai-praxis (2 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 495 tokens. 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.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.