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 hnikoloski/imlazy --skill imlazy-debuggit clone --depth 1 https://github.com/hnikoloski/imlazyWrote 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/hnikoloski/imlazy/imlazy-debug)<a href="https://agentmods.dev/skills/hnikoloski/imlazy/imlazy-debug"><img src="https://agentmods.dev/badge/skills/hnikoloski/imlazy/imlazy-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/hnikoloski/imlazy/imlazy-debug"><img src="https://agentmods.dev/badge/skills/hnikoloski/imlazy/imlazy-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 | $0.00038 | $0.00979 |
| Opus 5 | $0.00019 | $0.00490 |
| Sonnet 5 | $0.00008 | $0.00196 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
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 9d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
debugging
The Iron Law
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
If you have not completed Phase 1, you cannot propose fixes.
The Four Phases
You MUST complete each phase before proceeding to the next.
Phase 1: Root Cause Investigation
BEFORE attempting ANY fix:
-
Read error messages carefully. Don't skip past errors. Read stack traces completely. Note line numbers, file paths, error codes.
-
Reproduce consistently. Can you trigger it reliably? What are the exact steps? If not reproducible, gather more data before guessing.
-
Check recent changes. What changed that could cause this? git diff, recent commits, new dependencies, config changes.
-
Gather evidence in multi-component systems (CI → build → signing, API → service → DB): Before proposing fixes, add diagnostic instrumentation at each component boundary — log what data enters, log what data exits. Run once to see WHERE it breaks, then investigate that component. See
references/multi-component-debugging.mdfor a worked example. -
Trace data flow. Where does the bad value originate? What called this with the bad value? Keep tracing up until you find the source. Fix at source, not at symptom.
Phase 2: Pattern Analysis
- Find working examples — locate similar working code in the codebase.
- Read the reference implementation completely if implementing a pattern — don't skim.
- Identify differences — what's different between working and broken? List every difference.
- Understand dependencies — what config, environment, or state does this need?
Phase 3: Hypothesis and Testing
- Form one hypothesis: "I think X is the root cause because Y." Write it down. Be specific.
- Test minimally: make the smallest possible change to test the hypothesis. One variable at a time.
- Verify before continuing. Worked? → Phase 4. Didn't work? → form new hypothesis. Don't add more fixes on top.
- If you don't know, say "I don't understand X." Ask for help. Don't pretend.
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.
- 9d ago First seen · 91 lines · 38 tokens per session scan A 045ddcbbb78e
debugging is a skill published in the GitHub repository hnikoloski/imlazy (2 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 979 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 2026-08-31.
Other skills, from other repositories
bug-detective
This skill should be used when the user asks to "debug this", "fix this error", "investigate this bug", "troubleshoot this issue", "find the problem", "something is broken", "this isn't working", "why is this failing", or reports errors/exceptions/bugs. Provides systematic debugging workflow and common error patterns.
tfx-find
A codebase search tool for quickly locating files, functions, classes, variables, text, and project structure. A codebase is the collection of source files that make up a software project.
do-it-code-quality
Use when designing, changing, or debugging code to locate causal ownership and close the affected behavior.
debug
Debug a stubborn bug with a deterministic reproduction, hypothesis ledger, one-variable fixes, and a regression test. Use after the first obvious look fails, reproduction is unclear, or a fix attempt failed. Not for routine obvious failures; use for "ไล่บั๊ก".
bisect
Pinpoint the first bad commit for a reproducible regression in a safe temporary worktree. Use when HEAD is bad, a known revision is good, and one unattended command distinguishes them; handles flaky endpoints and git-bisect skip exit 125.
bug-finder
Hunt for previously unknown correctness defects in an existing repository by deriving invariants, prioritizing high-risk surfaces, generating concrete bug candidates, and proving or retiring them with bounded evidence. Use when the user asks to find bugs, hidden defects, races, lifecycle failures, data-loss paths, or…