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 CodeInfinity1/Stram --skill systematic-debugginggit clone --depth 1 https://github.com/CodeInfinity1/StramWrote 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/codeinfinity1/stram/systematic-debugging)<a href="https://agentmods.dev/skills/codeinfinity1/stram/systematic-debugging"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/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/codeinfinity1/stram/systematic-debugging"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/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 | $0.00028 | $0.00425 |
| Opus 5.5 | $0.00011 | $0.00170 |
| Sonnet 5.5 | $0.00006 | $0.00085 |
| Haiku 4.5 | $0.00003 | $0.00042 |
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
Purpose
Find root causes methodically. The assistant should collect current evidence, reproduce the problem when possible, form hypotheses, test them, patch narrowly, and verify the fix.
When To Use
Use for test failures, runtime errors, broken UI flows, flaky behavior, integration issues, CI failures, and "why does this not work" tasks.
Inputs And Evidence
- Error output, logs, failing command, expected behavior, recent changes, and environment.
- Source files, tests, config, runtime status, and reproduction steps.
- Verification command output after the fix.
Tool Map
read_filesearch_workspacerun_shell_commandpython_interpreterbrowser_live_observesystem_statuswrite_note
Workflow
- Reproduce or inspect the failure with current evidence.
- Define what "fixed" means before editing.
- Rank hypotheses from evidence, not keyword triggers.
- Inspect the smallest relevant code path.
- Make a scoped fix that preserves existing behavior.
- Run targeted verification and report residual risk.
Native Implementation Boundaries
- Use Stram tools and current repo commands.
- Do not import external reference debugging helpers or upstream scripts.
- Do not implement deterministic error-message-to-fix maps.
Safety And Approval
- Avoid destructive cleanup unless explicitly approved.
- Do not mask failures by weakening tests.
- Keep user changes intact.
Verification
- The failing command should pass or the remaining blocker should be proven.
- Add or update tests when risk warrants it.
- Report exact commands run and outcomes.
Failure Modes
- Patching the symptom while root cause remains.
- Over-broad refactors during debugging.
- Trusting stale logs.
References
- Shortlist item:
systematic-debugging. - Upstream inspiration: external reference systematic debugging reference only.
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 · 69 lines · 28 tokens per session scan A d825435a93be
systematic-debugging is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 425 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 2026-09-03.
Other skills, from other repositories
omh-live-incident-response
This is an OMH live-incident-response workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
debugging
Use this skill when something is broken and the cause is unknown — a failing test, a crash, an error message, wrong output, a regression, a hang, or behaviour that differs between environments — and it has to be found and fixed at the root. Also use it to build the failing proof for a suspected defect before fixing…
thinking-five-whys-plus
When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.
thinking-map-territory
When a claim, doc, test, metric, or assumption conflicts with observed behavior, stop theorizing from the map and verify the live code or data; let territory overrule.
debug-systematic
Systematic 4-phase debugging methodology for complex, intermittent, or mysterious issues. Use when investigating bugs, race conditions, or unexplained failures.
postmortem
Deliver a structured post-mortem after incidents, mistakes, or stuck sessions. Use when the user requests a structured post-mortem after incidents, mistakes, or stuck sessions.