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 skills add amplifthq/oh-my-dsh --skill systematic-debugginggit clone --depth 1 https://github.com/amplifthq/oh-my-dshWrote 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/skills/amplifthq/oh-my-dsh/systematic-debugging)<a href="https://agentmods.dev/skills/amplifthq/oh-my-dsh/systematic-debugging"><img src="https://agentmods.dev/badge/skills/amplifthq/oh-my-dsh/systematic-debugging/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/skills/amplifthq/oh-my-dsh/systematic-debugging"><img src="https://agentmods.dev/badge/skills/amplifthq/oh-my-dsh/systematic-debugging.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 | $0.00015 | $0.00156 |
| Opus 5.5 | $0.00006 | $0.00062 |
| Sonnet 5.5 | $0.00003 | $0.00031 |
| Haiku 4.5 | $0.00002 | $0.00016 |
Grade A, and why
systematic-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 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.
What it actually says
Systematic debugging
- Reproduce the exact symptom with the smallest safe command.
- Capture the complete error, inputs, environment, and boundary where expected behavior diverges.
- Form one falsifiable hypothesis at a time and test it with focused instrumentation or an existing diagnostic.
- Follow values backward to the first incorrect state; do not patch the last visible exception unless it is the cause.
- Add or identify a regression check that fails for the original bug.
- Make the smallest causal fix, rerun the regression check, then run proportionate surrounding checks.
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 · 15 lines · 15 tokens per session scan A d0e2dbfaaa88
systematic-debugging is a skill published in the GitHub repository amplifthq/oh-my-dsh (16 stars, last pushed 7d ago), licensed MIT. It adds 15 tokens to every session and 156 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 2026-08-30.
Other skills, from other repositories
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A troubleshooting guide for DeepSeek Harness, including its process, configuration, plugins, tools, skills, and model connections.
error-handling
A set of rules for deciding how software should report failures and what information error messages should contain.
ask-good-questions
Guidance for asking technical questions and reporting bugs so another developer can reproduce and answer them. It covers versions, environment details, minimal reproduction steps, expected and actual results, errors, and attempted fixes.
debug-systematically
A structured method for finding the underlying cause of a software problem. It moves from reproducing the problem, to locating the responsible code, to testing a specific explanation, and then to fixing it with a regression test.
perf-optimize
A performance-improvement guide that requires measuring real behaviour before changing code. It explains how to identify bottlenecks, test one change at a time, and check that the change did not break anything.
dsh-speed-up-perf
Use when investigating or optimizing DeepSeek Harness performance, designing realistic synthetic benchmarks or CI performance gates, profiling long Sessions or Web responsiveness, or turning performance PR evidence into measured behavior-preserving fixes.