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 agentmods add skills/altimateai/altimate-code/schema-migrationnpx skills add AltimateAI/altimate-code --skill schema-migrationgit clone --depth 1 https://github.com/AltimateAI/altimate-codeWhat 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 | $0.00034 | $0.01025 |
| Opus 5 | $0.00017 | $0.00513 |
| Sonnet 5 | $0.00007 | $0.00205 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
schema-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 2d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Schema Migration Analysis
Requirements
Agent: any (read-only analysis) Tools used: altimate_core_migration, altimate_core_schema_diff, schema_diff, read, glob, bash (for git operations)
When to Use This Skill
Use when the user wants to:
- Analyze a DDL migration for data loss risks before applying it
- Compare two schema versions to find breaking changes
- Review ALTER TABLE / CREATE TABLE changes in a PR
- Validate that a model refactoring doesn't break the column contract
Do NOT use for:
- Writing new models -> use
dbt-develop - Analyzing downstream impact of SQL logic changes -> use
dbt-analyze - Optimizing queries -> use
query-optimize
Workflow
1. Get the Schema Versions
For DDL migrations (ALTER TABLE, CREATE TABLE):
- Read the migration file(s) from disk
- The "old" schema is the current state; the "new" schema is after applying the migration
For dbt model changes (comparing before/after SQL):
# Get the old version from git
git show HEAD:<path/to/model.sql> > /tmp/old_model.sql
# The new version is the current file
For schema YAML changes:
- Read both versions of the schema.yml file
2. Analyze DDL Migration Safety
Call altimate_core_migration to detect data loss risks:
altimate_core_migration(old_ddl: <old_ddl>, new_ddl: <new_ddl>, dialect: <dialect>)
This checks for:
- Type narrowing: VARCHAR(100) -> VARCHAR(50) (truncation risk)
- NOT NULL without default: Adding NOT NULL column without DEFAULT (fails on existing rows)
- Dropped columns: Data loss if column has values
- Dropped constraints: Unique/check constraints removed (data integrity risk)
- Type changes: INTEGER -> VARCHAR (irreversible in practice)
- Index drops: Performance regression risk
3. Diff Schema Structures
For YAML/JSON schemas: Call altimate_core_schema_diff to compare two schema definitions:
altimate_core_schema_diff(schema1: <old_schema>, schema2: <new_schema>)
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.
- 2d ago First seen · 120 lines · 34 tokens per session scan A 4c88ec450264
schema-migration is a skill published in the GitHub repository AltimateAI/altimate-code (803 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 1,025 once invoked, about $0.0002 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 2026-08-30.
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