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.
git clone --depth 1 https://github.com/luanpdd/kit-mcpWrote 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/commands/luanpdd/kit-mcp/depurar)<a href="https://agentmods.dev/commands/luanpdd/kit-mcp/depurar"><img src="https://agentmods.dev/badge/commands/luanpdd/kit-mcp/depurar.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.01480 |
| Opus 5 | $0.00008 | $0.00740 |
| Sonnet 5 | $0.00003 | $0.00296 |
| Haiku 4.5 | $0.00002 | $0.00148 |
Grade A, and why
depurar 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 4d 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Papel do orquestrador: Coletar sintomas, invocar agente debugger, tratar checkpoints, invocar continuações.
Por que subagente: Investigação consome contexto rapidamente (ler arquivos, formar hipóteses, testar). Contexto fresco de 200k por investigação. Contexto principal permanece enxuto para interação com o usuário.
<available_agent_types> Tipos de subagente framework válidos (usar nomes exatos — não usar 'general-purpose'):
- debugger — Diagnostica e corrige problemas
- schema-checker — Pré-validação de SQL (FK, JOIN, INSERT) contra schema real via Supabase MCP. Use quando o bug envolve migration que falhou em apply ou suspeita de drift entre comentário do dev e schema real. </available_agent_types>
<supabase_pre_check>
Triagem rápida — bug envolve SQL/Supabase?
Se o $ARGUMENTS ou sintomas mencionam algum destes patterns, faça pre-validação com schema-checker ANTES de invocar o debugger genérico:
| Sintoma | Razão |
|---|---|
| "migration falhou em apply" | schema-checker valida FKs/colunas/tabelas — sintoma comum é referência a coluna/tabela inexistente |
| "RLS quebrou query" ou "query lenta após RLS" | Provavelmente auth.uid() sem (select) wrapper; veja skill supabase-rls-policies |
| "Edge Function quebrou em deploy" | Provavelmente bare specifier ou import sem versão; veja skill supabase-edge-functions |
| "user_metadata em policy" | Privilege escalation; veja skill supabase-rls-policies (REGRA absoluta) |
| "service_role exposto" | Vazamento via NEXT_PUBLIC_*; veja skill supabase-auth-ssr |
Se aplicável: invoque Task(subagent_type=schema-checker, prompt=...) primeiro. Se schema-checker retorna GO mas o bug persiste, então invoque o debugger.
</supabase_pre_check>
Verificar sessões ativas:
ls .planning/debug/*.md 2>/dev/null | grep -v resolved | head -5
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.
- 4d ago First seen · 191 lines · 15 tokens per session scan A 2d69a0c3b0b3
depurar is a command published in the GitHub repository luanpdd/kit-mcp (1 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 1,480 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 2026-09-03.
Other commands, from other repositories
qa-changes
This skill should be used when the user asks to "QA a pull request", "test PR changes", "verify a PR works", "functionally test changes", or when an automated workflow triggers QA validation of code changes. Provides a structured methodology for setting up the environment, exercising changed behavior, and reporting…
doctor
Diagnosticar y reparar problemas del framework Don Cheli, git y entorno. Usa cuando el usuario dice "doctor", "problemas del framework", "don cheli no funciona", "repair Don Cheli", "debug setup", "setup broken", "framework broken", "reparar entorno". Detecta y repara issues de configuración, git y dependencias…
fix
Universal debugging and fix application with semantic code analysis.
doctor
Badi configuration validation. Checks all Badi components and produces a diagnostic report.
http-service
Build, review or debug a Bun HTTP service. Loads the http-service skill, then works the task through its workflow.
gh-issue-use-cypress
Like /gh-issue-use-browser, but pinned to the Cypress MCP — use when your project runs the Cypress MCP for browser automation. Example — /gh-issue-use-cypress "Composer > Save" saving toasts failure but the record persists.