Borrowing it
Nothing to install: this file belongs to adityawrk/analytics-with-claude-code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/adityawrk/analytics-with-claude-code/main/.claude/skills/systematic-debug/SKILL.mdgit clone --depth 1 https://github.com/adityawrk/analytics-with-claude-codeWrote 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/adityawrk/analytics-with-claude-code/systematic-debug)<a href="https://agentmods.dev/skills/adityawrk/analytics-with-claude-code/systematic-debug"><img src="https://agentmods.dev/badge/skills/adityawrk/analytics-with-claude-code/systematic-debug/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/adityawrk/analytics-with-claude-code/systematic-debug"><img src="https://agentmods.dev/badge/skills/adityawrk/analytics-with-claude-code/systematic-debug.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 | $0.00064 | $0.01856 |
| Opus 5.5 | $0.00026 | $0.00742 |
| Sonnet 5.5 | $0.00013 | $0.00371 |
| Haiku 4.5 | $0.00006 | $0.00186 |
Grade A, and why
systematic-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 2mo 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging for Analytics
A 4-phase structured debugging methodology. Follow these phases in strict order. No shortcuts. No cargo-cult debugging. No "just try this and see."
Ground Rules
Read these first. They are non-negotiable.
- NEVER skip Phase 1. Do not attempt a fix before reproducing the error and reading the full output. No exceptions.
- NEVER make multiple changes at once. One variable at a time. If you change two things and the problem goes away, you do not know which one fixed it.
- 3-Strike Rule. After 3 failed fix attempts, STOP. Summarize what you have tried, what you have learned, and escalate to the user. Do not keep guessing.
- State your hypothesis. Before every fix attempt, tell the user what you believe is wrong and why. "I think X because Y, so I will try Z."
- Clean up after yourself. Remove all debug instrumentation (extra logging, LIMIT clauses, temp tables, print statements) before declaring the issue resolved.
Phase 1: Reproduce and Gather Evidence
Goal: See the failure with your own eyes. Understand exactly what is happening before forming any opinion about why.
Steps
-
Run the failing query or script exactly as reported.
- Use the same database, schema, and role if possible.
- Do not modify the query before running it.
- Capture the full error output — not just the first line.
-
Read the complete error message.
- Copy the full stack trace or error output.
- Identify the specific line, column, or object that failed.
- Note the error code if one is provided.
-
Check the environment.
- What database/warehouse is this running against?
- What schema or dataset is active?
- Are there any session-level settings (timezone, role, warehouse size)?
-
Check data freshness. (Analytics-specific)
- When was the source data last updated?
- Is the failure caused by stale or missing data rather than a code bug?
- Run
SELECT MAX(updated_at)or equivalent on key source tables.
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.
- 2mo ago First seen · 197 lines · 64 tokens per session scan A c5555331b000
systematic-debug is a skill published in the GitHub repository adityawrk/analytics-with-claude-code (6 stars, last pushed 8mo ago), licensed MIT. It adds 64 tokens to every session and 1,856 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
debugging-dbt-errors
Debugs and fixes dbt errors systematically. Use when working with dbt errors for: (1) Task mentions "fix", "error", "broken", "failing", "debug", "wrong", or "not working" (2) Compilation Error, Database Error, or test failures occur (3) Model produces incorrect output or unexpected results (4) Need to troubleshoot…
refactoring-dbt-models
Safely refactors dbt models with downstream impact analysis. Use when restructuring dbt models for: (1) Task mentions "refactor", "restructure", "extract", "split", "break into", or "reorganize" (2) Extracting CTEs to intermediate models or creating macros (3) Modifying model logic that has downstream consumers (4)…
datahub-verified-remediation
Use this skill when a source schema change has broken, or is about to break, a downstream transformation and the user wants a fix they can merge — not a summary. Triggers on: "a column was renamed, fix the dbt model", "this field is gone downstream", "schema drift", "our model still selects the old column", "generate…
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.
cookie-debugging
Uses Chrome DevTools MCP for inspecting, debugging, and testing cookies, session state, authentication issues, and cookie consent compliance. Use when diagnosing 401/403 errors, authentication redirects, session expiration, Cookie/Set-Cookie header issues, cookie banner consent conformance, or third-party…
a11y-debugging
Uses Chrome DevTools MCP for accessibility (a11y) debugging and auditing based on web.dev guidelines. Use when testing semantic HTML, ARIA labels, focus states, keyboard navigation, tap targets, and color contrast.