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 SethGammon/Citadel --skill systematic-debugginggit clone --depth 1 https://github.com/SethGammon/CitadelWrote 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/sethgammon/citadel/systematic-debugging)<a href="https://agentmods.dev/skills/sethgammon/citadel/systematic-debugging"><img src="https://agentmods.dev/badge/skills/sethgammon/citadel/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/sethgammon/citadel/systematic-debugging"><img src="https://agentmods.dev/badge/skills/sethgammon/citadel/systematic-debugging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.01276 |
| Opus 5.5 | $0.00018 | $0.00510 |
| Sonnet 5.5 | $0.00009 | $0.00255 |
| Haiku 4.5 | $0.00005 | $0.00128 |
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.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/systematic-debugging — Root Cause Before Fix
Orientation
Use when: root cause is unknown and premature fixes keep failing -- enforces observe -> hypothesize -> verify before touching code. Don't use when: root cause is already known (use /marshal to implement the fix); the bug is shallow and the stack trace is enough (use /do).
Protocol
Phase 1: OBSERVATION & REPRODUCTION
- Read the error message, stack trace, or bug description
- Reproduce the issue:
- If it's a type error: run typecheck and read the full error
- If it's a runtime error: identify the triggering conditions
- If it's a behavioral bug: document expected vs actual behavior
- Isolate the failing component/function:
- What file? What function? What line?
- What are the inputs when it fails?
- Does it fail consistently or intermittently?
Output: A clear problem statement: "{Component} does {X} when it should do {Y}, triggered by {condition}"
Phase 2: HYPOTHESIS & VERIFICATION
-
Formulate up to 3 hypotheses for WHY the bug exists:
- H1: {most likely cause} — because {evidence}
- H2: {second candidate} — because {evidence}
- H3: {third candidate} — because {evidence}
-
For each hypothesis, define a verification step:
- Add a console.log / diagnostic read / breakpoint
- Check a specific value at a specific point
- DO NOT change any logic yet — only observe
-
Run the verification:
- Which hypothesis was confirmed?
- Which were eliminated?
- If none confirmed: formulate new hypotheses with the new information
CRITICAL: Do not skip this phase. Do not "just try" a fix. Verify first.
Phase 3: ROOT CAUSE ANALYSIS
Once a hypothesis is confirmed:
- Explain WHY the bug happens, not just WHERE:
- Trace the data flow backward from the symptom to the source
- Identify the specific incorrect assumption or logic error
- Document the causal chain: "A calls B with X, B assumes X > 0, but A passes -1 when {condition}"
What ships with it
2 files 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.
- 1mo ago First seen · 144 lines · 45 tokens per session scan A f673e7bf5f8e
systematic-debugging is a skill published in the GitHub repository SethGammon/Citadel (923 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 1,276 once invoked, about $0.0002 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
zapier-status
Check the health of your Zapier MCP setup. Three modes — health check (dashboard view), audit (find waste and duplicates), diagnose (systematic troubleshooting). Use when asking "is my MCP working?", "check my tools", "audit my setup", "what's broken?", or "zapier status".
audit-project
Run an iterative multi-agent code audit until critical and high findings are resolved. Use when the user says "audit my code", "find all the bugs", "deep code audit", "iterative review", or "review until clean".
root-cause
Find the mechanism behind a failure instead of patching its symptom - reproduce first, one variable per experiment with the prediction written before the run, exit by naming the mechanism and pinning it with a failing test. Use for a bug, an unexplained red test, or a failure that will not reproduce.
discovery
Use this skill when running systematic quality discovery and issue detection. Runs modular probes adapted to the project's tech stack, presents findings interactively for user triage, and creates VCS issues for confirmed problems. Invoked standalone via /discovery or embedded in session-end.
claude-md-drift-check
Use when detecting drift between CLAUDE.md (or AGENTS.md, the Codex CLI alias) / meta narrative and live repository state. Ten checks: absolute-path resolution, 01-projects/ count claims, issue-reference freshness, session-file existence, command-count sync, session-config-parity (mandatory template keys = error…
debug
Use when encountering any bug, test failure, build break, or unexpected behavior — runs a 4-phase systematic debugging process before proposing any fix. Iron Law: NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST. Produces a .orchestrator/debug/ artifact the fixer agent must reference.