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 h4vzz/awesome-ai-agent-skills --skill database-migrationgit clone --depth 1 https://github.com/h4vzz/awesome-ai-agent-skillsWrote 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/h4vzz/awesome-ai-agent-skills/database-migration)<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/database-migration"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/database-migration/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/h4vzz/awesome-ai-agent-skills/database-migration"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/database-migration.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 | $0.00034 | $0.02112 |
| Opus 5 | $0.00017 | $0.01056 |
| Sonnet 5 | $0.00007 | $0.00422 |
| Haiku 4.5 | $0.00003 | $0.00211 |
Grade A, and why
database-migration 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 10d 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.
This is a copy
92% identical to database-migration — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Migration
This skill enables an AI agent to manage versioned database schema changes through migration frameworks. The agent creates forward and rollback migration scripts, handles data backfills during schema changes, ensures zero-downtime deployments with safe migration patterns, and integrates migration workflows into CI/CD pipelines. It supports major tools including Alembic (Python/SQLAlchemy), Prisma Migrate (TypeScript/Node), Flyway (Java/SQL), and Knex (JavaScript).
Workflow
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Assess the schema change: Analyze the requested change — adding columns, creating tables, modifying constraints, renaming fields, or transforming data. Classify the change as backward-compatible (additive) or breaking (destructive) to determine the deployment strategy. Breaking changes require a multi-phase migration approach.
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Select the migration tool: Choose the appropriate migration framework based on the project's tech stack. Use Alembic for Python/SQLAlchemy projects, Prisma Migrate for TypeScript/Prisma projects, Flyway for Java or SQL-first workflows, and Knex for Node.js/Express projects. Ensure the tool is initialized and connected to the target database.
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Generate the migration script: Auto-generate a migration from schema diffs where supported (Alembic autogenerate, Prisma migrate dev), then review and edit the generated script. Add explicit rollback (downgrade) logic. For data backfills, include the data transformation within the migration to keep schema and data changes atomic.
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Test in a staging environment: Apply the migration against a staging database that mirrors production. Verify that the migration applies cleanly, that existing queries still work, and that the rollback restores the previous state. Run the application's test suite against the migrated schema.
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Deploy with zero-downtime strategy: For production, use expand-and-contract migrations. Phase 1: add new columns/tables (expand) without removing old ones. Phase 2: deploy application code that writes to both old and new structures. Phase 3: backfill data. Phase 4: deploy code using only new structures. Phase 5: remove old columns/tables (contract). This ensures no downtime and safe rollback at each phase.
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.
- 10d ago First seen · 175 lines · 34 tokens per session scan A a8371a5ee7a0
database-migration is a skill published in the GitHub repository h4vzz/awesome-ai-agent-skills (34 stars, last pushed yesterday), licensed MIT. It adds 34 tokens to every session and 2,112 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to database-migration, differing in 2 lines, and is treated as a copy.
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