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 skills/avmnu-sng/sutra/debuggingnpx skills add avmnu-sng/sutra --skill debugginggit clone --depth 1 https://github.com/avmnu-sng/sutraWhat 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 | $0.00045 | $0.02187 |
| Opus 5 | $0.00023 | $0.01094 |
| Sonnet 5 | $0.00009 | $0.00437 |
| Haiku 4.5 | $0.00005 | $0.00219 |
Grade A, and why
debugging 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 2d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging
Find the defect by evidence, not by intuition. A bug is a gap between what the code does and what you believe it does; debugging is the disciplined closing of that gap. Trace before you theorize -- read the actual behavior first, and let every step be driven by an observation you can point at, never by a hunch about which layer "feels wrong."
Work the steps in order. The order is load-bearing: reproduce before you change anything, localize before you explain the mechanism, and prove causation before you declare victory.
When to use / When not to
- Use when a test is red for an unknown reason, a system is misbehaving in production, output is wrong, something is intermittent, or a change broke something and you do not yet know what.
- Do not use for known, mechanical fixes (a typo, a clear null check a reviewer already pointed at) where there is no isolation work to do. This is for defects whose cause is not yet established.
0. If it is on fire, stop the bleeding first
A live production incident is not a debugging session. A running system serving users is not a debugger -- you cannot single-step it, and every minute spent root-causing is a minute of user-facing damage. Contain first, investigate after.
Contain. Reach for the fastest reversible lever that stops the harm:
- Roll back to the last known-good release.
- Flip the feature flag off for the broken path.
- Divert or shed traffic (drain the bad instance, fail over, rate-limit).
- Disable the offending job, consumer, or integration.
Pick the lever with the smallest blast radius that actually stops the bleeding. Rollback is usually safest because it is reversible and well-understood; a forward "quick fix" pushed under pressure is itself an unreviewed change.
Preserve evidence before you wipe state. Capture logs, a stack trace, the current config, and a snapshot of the bad state before the rollback erases it. You still have to root-cause afterward, and the incident is your best reproduction.
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.
- 2d ago First seen · 203 lines · 45 tokens per session scan A 23f84f84fcc3
debugging is a skill published in the GitHub repository avmnu-sng/sutra (2 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 2,187 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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