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 fall-out-bug/sdp --skill debuggit clone --depth 1 https://github.com/fall-out-bug/sdpWrote 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/fall-out-bug/sdp/debug)<a href="https://agentmods.dev/skills/fall-out-bug/sdp/debug"><img src="https://agentmods.dev/badge/skills/fall-out-bug/sdp/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/fall-out-bug/sdp/debug"><img src="https://agentmods.dev/badge/skills/fall-out-bug/sdp/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 | $0.00014 | $0.00548 |
| Opus 5.5 | $0.00006 | $0.00219 |
| Sonnet 5.5 | $0.00003 | $0.00110 |
| Haiku 4.5 | $0.00001 | $0.00055 |
Grade A, and why
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 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@debug - Systematic Debugging
Evidence-based debugging using scientific method. Not "try stuff and see" -- systematic investigation.
EXECUTE THIS NOW
When user invokes @debug "<issue>":
Phase 1: OBSERVE - Gather Facts
Goal: Collect evidence WITHOUT forming hypotheses
Actions:
- Read error messages/logs completely
- Check git diff for recent changes
- Verify environment (Python version, dependencies)
- Check configuration files
- Reproduce the bug consistently
Output: Observation log with timestamps, error messages, environment state
Phase 2: HYPOTHESIZE - Form Theories
Goal: Create testable theories about root cause
Process:
- List ALL possible causes (brainstorm)
- Rank by likelihood (use evidence)
- Select TOP theory to test first
- Define falsification test
Output: Hypothesis list with ranked theories
Phase 3: EXPERIMENT - Test Theories
Goal: Run targeted tests to confirm/deny hypotheses
Actions:
- Design minimal experiment
- Run ONLY the experiment
- Record result objectively
- Move to next hypothesis if denied
Output: Experiment results with pass/fail
Phase 4: CONFIRM - Verify Root Cause
Goal: Confirm root cause and verify fix
Actions:
- Reproduce bug with root cause isolated
- Implement minimal fix
- Verify fix resolves issue
- Add regression test
Output: Root cause report + fix
When to Use
- Tests failing unexpectedly
- Production incidents
- Bug reports with unclear cause
- Performance degradation
- Integration failures
Common Pitfalls
| Pitfall | Problem |
|---|---|
| Skipping observation | Jumping to conclusions |
| Testing multiple things | Can't isolate cause |
| Confirmation bias | Only looking for proving evidence |
| Stopping at first fix | Not understanding WHY it worked |
Exit Criteria
- Root cause identified
- Fix implemented and verified
- Regression test added
See Also
@bugfix- Quality bug fixes (P1/P2)@hotfix- Emergency fixes (P0)@issue- Bug classification and routing
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 · 106 lines · 14 tokens per session scan A 7b69f169b205
debug is a skill published in the GitHub repository fall-out-bug/sdp (19 stars, last pushed 4mo ago), licensed MIT. It adds 14 tokens to every session and 548 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
norma-workflow
Run every coding task through Norma's deterministic checks and record the outcome to the audit trail. Use whenever you create or modify code in a workspace connected to the Norma MCP server, when asked to review code against organization standards, or when asked to work through the repository's open issues.
codebase-refactoring
Three-part workflow to improve overall codebase health with jscpd — find and fix duplicated code, find and remove or refactor dead code, then find and simplify the largest/most complex files. Starts from --dashboard/--health to prioritize and ends by re-measuring the score.
prismer-python-debugpy
Debug Python: pdb REPL + debugpy remote (DAP).
debug-live
Guides root-cause investigations with debugging capabilities by setting breakpoints, starting a debug session, stepping through execution, inspecting variables, and tracing symptoms back to their origin. Prefer it for runtime bugs, failing tests, exceptions, crashes, hangs, wrong/null values, and unexpected output…
remove-deadcode
Remove unused code from this project with ultrawork mode, LSP-verified safety, atomic commits. Triggers: remove dead code, dead code, cleanup, remove unused.
webapp-qa
Perform scoped exploratory QA of a web application, reproduce defects, collect screenshots and console evidence, and deliver a prioritized report.