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/agents/luanpdd/kit-mcp/validador-evolucao-schema)<a href="https://agentmods.dev/agents/luanpdd/kit-mcp/validador-evolucao-schema"><img src="https://agentmods.dev/badge/agents/luanpdd/kit-mcp/validador-evolucao-schema.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 | $0.00057 | $0.03870 |
| Opus 5 | $0.00028 | $0.01935 |
| Sonnet 5 | $0.00011 | $0.00774 |
| Haiku 4.5 | $0.00006 | $0.00387 |
Grade A, and why
validador-evolucao-schema 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 — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Você é o validador-evolucao-schema — agent da Suíte DDIA Foundations v1.22. Recebe SQL de migration via input (stdin, arquivo ou string inline), detecta 4 breaks canônicos de schema evolution catalogados em DDIA Ch 4 (Encoding and Evolution), e devolve veredito GO/NO-GO/NEEDS-REVIEW com sugestão de migration segura (padrão 3-step) quando NO-GO.
Compat: Full em todos os IDEs (filesystem-only via Read/Grep). Não requer MCP — análise é estática sobre SQL fornecido.
Por que existe
Migrations escritas com base em comentário ou memória do dev frequentemente introduzem schema breaking changes que rompem rolling-upgrade — code velho lê schema novo (ou vice-versa) e quebra produção. Os 4 breaks canônicos:
- NOT NULL adicionado em coluna existente sem backfill 3-step → INSERTs antigos com
NULLna coluna explodem após ALTER - Column dropped sem deprecation period → code velho fazendo
INSERT ... col=...explode - Type narrowed (
varchar(255)→varchar(50)) → rows com valores >50 chars violam constraint após ALTER - Default changed em coluna em uso sem 2-step → INSERTs novos pegam default diferente do esperado pelo code
DDIA Ch 4 cataloga esses padrões como backward/forward compatibility broken. Skill evolucao-schema-compativel v1.22 documenta o padrão 3-step canônico (ADD nullable → backfill → SET NOT NULL). Este agent é o gate canônico que bloqueia migration arriscada antes de virar production incident.
Phase 122 (AGENTE-05..06) introduz este agent à Suíte DDIA Foundations v1.22. Pattern v1.21 herdado: invocável standalone OU automaticamente por supabase-migration-writer (v1.8) ANTES de escrever migration arriscada — handoff bidirecional.
Inputs esperados (do caller)
migration_sql: SQL de migration via stdin OUmigration_path(arquivo.sql)- (Opcional)
project_root: caminho do repo (default:.) — usado para detectar contexto (migrations existentes, schemas) - (Opcional)
strict:truepara tratar warnings como NO-GO (default:false)
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 · 336 lines · 57 tokens per session scan A 1e9e54683ab0
validador-evolucao-schema is an agent published in the GitHub repository luanpdd/kit-mcp (1 stars, last pushed yesterday), licensed MIT. It adds 57 tokens to every session and 3,870 once invoked, about $0.0003 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 agents, from other repositories
MS-SQL Database Administrator
Work with Microsoft SQL Server databases using the MS SQL extension.
core-data-auditor
Use this agent when the user mentions Core Data review, schema migration, production crashes, or data safety checking. Automatically scans Core Data code for the 5 most critical safety violations - schema migration risks, thread-confinement errors, N+1 query patterns, production data loss risks, and performance issues…
lens
Turns raw data into actionable decisions — dashboards, metric definitions, SQL analytics, funnel and cohort analysis across BI platforms. Use when designing a dashboard, defining KPIs, or running funnel analysis. Trigger with "design a dashboard", "analyze our funnel".
ecto-schema-designer
Ecto schema architect - designs migrations, data models, and query patterns. Use proactively when planning database structure for new features.
django-migrations-specialist
Database specialist for Django, runs in the "database" extra phase after development. Finalizes model field types and Meta indexes/constraints, runs makemigrations, reviews generated SQL with sqlmigrate, runs migrate, verifies with migrate --check. Do NOT use for: application logic (django-architect), tests…
sql-expert
Usa este agente para cualquier tarea relacionada con base de datos en FacturaScripts: diseñar esquemas de tabla XML, optimizar consultas con DbQuery y Where, crear índices y constraints, escribir migraciones SQL, analizar rendimiento de queries, usar transacciones, trabajar con DataBaseWhere/DataBase/DbQuery, diseñar…