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 saemihemma/lead-producer-oss --skill workflow-systematic-debugginggit clone --depth 1 https://github.com/saemihemma/lead-producer-ossWrote 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/saemihemma/lead-producer-oss/workflow-systematic-debugging)<a href="https://agentmods.dev/skills/saemihemma/lead-producer-oss/workflow-systematic-debugging"><img src="https://agentmods.dev/badge/skills/saemihemma/lead-producer-oss/workflow-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/saemihemma/lead-producer-oss/workflow-systematic-debugging"><img src="https://agentmods.dev/badge/skills/saemihemma/lead-producer-oss/workflow-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 | $0.00043 | $0.00663 |
| Opus 5 | $0.00022 | $0.00331 |
| Sonnet 5 | $0.00009 | $0.00133 |
| Haiku 4.5 | $0.00004 | $0.00066 |
Grade A, and why
workflow-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 8d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging Workflow
Purpose
Find root cause before code changes. Turn unclear failures into confirmed causes, smallest-fix recommendations, or explicit escalation.
Use When
- Bug or failure is real but the cause is unclear
- Need reproduction, code tracing, and hypothesis testing before fixing
- Investigation should happen before packaging, implementation, or broader review
- Recent regressions or intermittent failures need a disciplined debug path
Do NOT Use When
- Live production incident (use
workflow-incident-response) - Root cause is already understood and only needs packaging or handoff (use
workflow-issue-triage) - User wants direct implementation and the failing behavior is already clear
- Task is feature planning, architecture review, or proactive audit
Workflow
- Capture symptom, environment, and current behavior.
- Confirm or tighten reproduction status.
- Build a feedback loop first. Before hypothesizing, build the cheapest fast, deterministic, agent-runnable loop that reliably shows the failure (pass/fail in seconds). A bug with a good loop is most of the way to fixed. See
references/feedback-loops.mdfor the ladder of techniques. If no loop is reachable, say so and focus on evidence-gathering. - Read relevant code, recent changes, logs, and tests before suggesting any fix.
- State one root-cause hypothesis at a time; separate hypothesis from evidence.
- Test the hypothesis against the loop. If false, discard it and form the next one.
- If confirmed, recommend the smallest fix that removes the cause; the loop becomes the regression test.
- After 3 failed hypotheses, stop and escalate instead of guessing.
Reference Map
references/feedback-loops.md- the 10-rung ladder for building a fast, deterministic, agent-runnable reproduction loop
Default Output
DEBUGGING REPORT
================
Symptom: what is failing, where, and under what conditions
Feedback Loop: the command/test that reliably reproduces it, or why none is reachable
Reproduction: confirmed / partial / not yet reliable
Root Cause: confirmed cause or current best hypothesis
Evidence: code path, logs, diffs, or repro evidence supporting the conclusion
Next Step: smallest fix, further evidence needed, or escalation
Regression Test: behavior to lock in once fixed
Status: confirmed / investigating / escalated
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 60 lines · 43 tokens per session scan A ef5737fd5778
workflow-systematic-debugging is a skill published in the GitHub repository saemihemma/lead-producer-oss (2 stars, last pushed 8d ago), licensed MIT. It adds 43 tokens to every session and 663 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 2026-09-03.
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