getkimchi/kimchi is a terminal-based coding agent that helps with software development through Kimchi’s language-model infrastructure. It can run tasks with one selected model or coordinate multiple models, with model roles chosen by its orchestration system.
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 getkimchi/kimchi --skill dap-debugginggit clone --depth 1 https://github.com/getkimchi/kimchiWrote 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/getkimchi/kimchi/dap-debugging)<a href="https://agentmods.dev/skills/getkimchi/kimchi/dap-debugging"><img src="https://agentmods.dev/badge/skills/getkimchi/kimchi/dap-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/getkimchi/kimchi/dap-debugging"><img src="https://agentmods.dev/badge/skills/getkimchi/kimchi/dap-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 | $0.00037 | $0.02290 |
| Opus 5.5 | $0.00015 | $0.00916 |
| Sonnet 5.5 | $0.00007 | $0.00458 |
| Haiku 4.5 | $0.00004 | $0.00229 |
Grade A, and why
dap-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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging with DAP Tools
Use this skill when you need runtime state — a value at a line, the exception that actually threw, which code path ran — and reading the source no longer answers the question.
Per-language launch config, source mapping, and expression syntax rules live
in reference files alongside this skill. Load the one matching your debuggee
before launching:
skill_view name="dap-debugging" file_path="references/go.md",
references/python.md, references/typescript.md, or
references/native.md.
The debugging loop
Debugging is a search: you are locating the first place observable state diverges from intended state. Each iteration narrows the search.
- Reproduce and name the symptom. Run the program normally first
(
bash). Write down the visible wrong thing: wrong output, exception, hang. The symptom anchors every breakpoint you set. - State your one-line hypothesis. "The cache returns a stale entry after eviction." One line, about data. If you cannot, read more code — debugging without a hypothesis is random walking.
- Probe the boundary where the symptom appears. Breakpoint at the observable wrong behavior (see placement rules below), inspect state. Ask: does it match expectations here?
- Move backward along the data flow. State is wrong at your probe → the corruption happened earlier. Find where the bad value was written (assignment site, mutation, argument pass) and probe there. Repeat until you reach a probe where state is correct — the divergence is between the last correct and first incorrect probe.
- Minimize the step distance. Steps between your last-correct and
first-wrong probes may still be large. Step (
step_over/step_in) through that window while re-evaluating the suspect expression. The statement where the expression flips from right to wrong is usually the bug — or one line away from it. - Fix, then verify at the same breakpoint. Re-run to the same probe with the fix and confirm state is now correct. Do not skip the verification pass.
What ships with it
4 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 · 187 lines · 37 tokens per session scan A df5507c2b220
dap-debugging is a skill published in the GitHub repository getkimchi/kimchi (2,276 stars, last pushed today), licensed Apache-2.0. It adds 37 tokens to every session and 2,290 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.
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