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 agentmods add skills/porcupine-md/jonggrang/debugging-systematicallynpx skills add porcupine-md/jonggrang --skill debugging-systematicallygit clone --depth 1 https://github.com/porcupine-md/jonggrangWhat 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 | $0.00026 | $0.00746 |
| Opus 5 | $0.00013 | $0.00373 |
| Sonnet 5 | $0.00005 | $0.00149 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
debugging-systematically 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 2d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The 6-Step Debugging Protocol
Step 1: Reproduce Reliably
Before anything else, make the bug reproducible.
# Write a failing test that reproduces the bug
it('reproduces bug #123', async () => {
// The exact scenario that causes the bug
const result = await service.doThing(buggyInput);
expect(result).toBe(expectedValue); // This fails currently
});
If you can't write a reproducible test, you don't understand the bug yet.
Step 2: Read the Error
Read the FULL error message + stack trace. Most bugs tell you exactly where they are.
Checklist:
- What file and line number?
- What was the actual value vs expected?
- Is there an inner error wrapped in the outer one?
Step 3: Narrow the Scope (Binary Search)
Full system broken?
→ Is it the database connection or the business logic?
→ Is it in the controller or the service?
→ Is it in the query or the parsing?
Add console.log / breakpoints to establish:
- What inputs enter the broken function?
- What does the function actually return?
Step 4: Form a Hypothesis
State your hypothesis explicitly:
"I believe the bug is caused by [X] because [evidence Y]."
Common hypotheses:
- Off-by-one error
- Async/await missing (uncaught promise)
- Null/undefined not handled
- Type coercion (== vs ===)
- Race condition
- Stale cache/state
Step 5: Verify (Don't Fix Yet)
Prove your hypothesis is correct BEFORE fixing:
// Add assertion to confirm hypothesis
console.assert(typeof userId === 'string', `userId is ${typeof userId}`);
If the hypothesis is wrong, go back to Step 3.
Step 6: Fix and Confirm
- Apply the minimal fix
- Run the reproduction test — it should now pass
- Run the full test suite — nothing should break
- Write a regression test if one didn't exist
Common Bug Patterns
Async bugs:
// BUG: forgot await
const user = getUser(id); // returns Promise, not User
user.name; // undefined
// FIX:
const user = await getUser(id);
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.
- 2d ago First seen · 122 lines · 26 tokens per session scan A e35911443ba4
debugging-systematically is a skill published in the GitHub repository porcupine-md/jonggrang (11 stars, last pushed 6d ago), licensed MIT. It adds 26 tokens to every session and 746 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…