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 ariaxhan/kernel-claude --skill debuggit clone --depth 1 https://github.com/ariaxhan/kernel-claudeWrote 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/ariaxhan/kernel-claude/debug)<a href="https://agentmods.dev/skills/ariaxhan/kernel-claude/debug"><img src="https://agentmods.dev/badge/skills/ariaxhan/kernel-claude/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/ariaxhan/kernel-claude/debug"><img src="https://agentmods.dev/badge/skills/ariaxhan/kernel-claude/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 | $0.01746 |
| Opus 5.5 | $0.00026 | $0.00698 |
| Sonnet 5.5 | $0.00013 | $0.00349 |
| Haiku 4.5 | $0.00006 | $0.00175 |
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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Diagnosis comes before prescription: a surgeon cutting before the X-ray is guessing with a
knife. Two modes, same discipline. bug (default) is the steps below. refactor swaps the
subject from a failure to a structure, and produces a plan instead of a fix.
Run agentdb recall with the exact error text, subsystem/library, failing
test, and known files/symbols. Recall again when the hypothesis changes or a new failure
appears; that is a new retrieval question. Reference on demand:
skills/debug/reference/debug-research.md.
-
HYPOTHESIZE: list 3 causes before pursuing any.
- Read ALL error output first (anchoring bias mitigation).
- Write each hypothesis to AgentDB. Prevents circular re-investigation.
- (gate: 3 candidate hypotheses written; none pursued yet)
-
ISOLATE: binary search, O(log n) not O(n).
- Code: call chain A→B→C→D→E fails → check midpoint C → recurse into failing half.
- Time:
git bisectbetween known-good and known-bad commit. ~10 tests for 1000 commits. - Input: large failing input → split in half → recurse to minimal reproduction case.
- Instrument at boundaries: log inputs/outputs at each layer boundary.
- Mock external dependencies to isolate which one causes failure.
-
Diff working vs failing state (env, config, input, commit) before theorizing.
-
Flaky test: classify first as timing/race, shared state, unseeded randomness, or environment difference; only then propose a fix.
-
(gate: failure localized to a specific function/commit/input subset)
-
ROOT CAUSE: the error line is the FAILURE. The DEFECT is upstream.
- Ask: what assumption was violated? What invariant broke?
- If you can't explain WHY it broke, you haven't found root cause.
- Top causes by frequency: wrong input shape/type · off-by-one · missing null check · race condition · shared-state mutation · wrong comparison operator · variable scope · swallowed error · API contract mismatch · environment difference.
- (gate: can state root cause in one sentence explaining the violated invariant)
-
FIX: root cause, not symptom.
- Fix the DEFECT, not the FAILURE site. (Null check at crash site = symptom fix.)
- Write regression test that fails before fix, passes after.
- Run: original failing case + edge cases + full regression suite.
- Commit fix + test together.
- (gate: regression test green; original failing case passes)
<refactor_mode> Triggers: refactor, restructure, clean up, coupling, dependency, "what breaks if". Same rule: diagnose, then hand off. Do not start cutting inside this mode.
- MAP: every file/module touching the target. Grep/Glob every reference, or
graphify affected <symbol>when the graph is fresh. Build the import/call map. - TRACE DEPS: per file, who calls it, who depends on it, what breaks if it changes.
- MEASURE COUPLING: cross-module reference counts, circular dependencies, the
per-function CCN from
scripts/complexity.sh. - RISKS: current edge cases, what is tested, what is not, invariants to preserve.
- PLAN: files in change order, tests that must pass before AND after, tier by reversibility x blast radius (file count is only a weak hint). Hand off to /kernel:simplify to execute, which owns the preservation contract and the gate. </refactor_mode>
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.
- 1mo ago Changed · +3 lines dc32fc23fad8
- 1mo ago Changed · +5 lines 37ec335142db
- 1mo ago Changed · +39 lines · +12 tokens per session 1c2f989607e0
- 1mo ago First seen · 88 lines · 52 tokens per session scan A 18939e83b03c
debug is a skill published in the GitHub repository ariaxhan/kernel-claude (14 stars, last pushed 2d ago), licensed MIT. It adds 64 tokens to every session and 1,746 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 2026-08-30.
Other skills, from other repositories
Diagnose
When something feels off, type /diagnose and describe the symptom. The skill walks the seven-layer stack (kernel, skills, hooks, daemons, vault, doctrine, principal config) and reports which layer is most likely responsible. Caddy pattern applied to debugging.
Stuck
Walk the 6-rung escalation ladder before declaring stuck or asking the principal. Most "stuck" is actually "haven't tried the next approach." Stopping is the last resort, not the first response.
First 10 Moves
The exact operational recon sequence for an unfamiliar codebase or unfamiliar area. Replaces "ask the human to clarify" with "read the code first." Most clarification questions are answered by 5 minutes in the relevant file - this skill enforces reading before asking.
learn-from-failure
When a failure occurs, classify it, check for repetition, and produce a durable artifact that prevents recurrence.
solution-hunt
When blocked, systematically search for legitimate alternate routes before declaring inability.
system-check
Read-only installation smoke test for skills, daemons, operational memory, cognitive runtime, nightly freshness, terminal evidence, and unique route ownership.