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 catpilotai/catpilot-ai-guardrails --skill database-safetygit clone --depth 1 https://github.com/catpilotai/catpilot-ai-guardrailsWrote 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/catpilotai/catpilot-ai-guardrails/database-safety)<a href="https://agentmods.dev/skills/catpilotai/catpilot-ai-guardrails/database-safety"><img src="https://agentmods.dev/badge/skills/catpilotai/catpilot-ai-guardrails/database-safety/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/catpilotai/catpilot-ai-guardrails/database-safety"><img src="https://agentmods.dev/badge/skills/catpilotai/catpilot-ai-guardrails/database-safety.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 | $0.00075 | $0.03748 |
| Opus 5 | $0.00037 | $0.01874 |
| Sonnet 5 | $0.00015 | $0.00750 |
| Haiku 4.5 | $0.00007 | $0.00375 |
Grade A, and why
database-safety 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.
How it starts
The opening of the file, as written. The whole thing — 414 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Why
Database state is the asset that survives every deploy. Compute can be rebuilt from images in minutes; rows cannot be rebuilt from anywhere except the last backup. Most catastrophic AI-assisted incidents at the database layer follow the same three shapes:
- A
DELETEorUPDATEruns without aWHEREclause because the model treated "delete the old test rows" as a sentence rather than a query. Every row in the table is touched in one statement and the transaction commits before anyone notices. - A migration runs straight against production with no dry-run, no staging dress rehearsal, no rollback file. The schema change succeeds on the structure but breaks an index, a foreign key, or an application assumption, and the only way back is point-in-time recovery.
- A query is built by string-concatenating user input into SQL, producing a working feature that also produces an injection vector the first time an attacker sends a quote character.
These are not language-specific or framework-specific failures. They occur
in raw psql, in ORMs, in serverless functions calling RDS, in
prisma db push --accept-data-loss, and in manage.py shell one-liners.
This skill applies the same six-step protocol the cloud-cli-safety skill
applies to infrastructure: never modify state you have not first
queried, counted, and shown to the user.
When to apply
Apply this skill before the agent runs, recommends, or commits any of the following:
- Direct SQL execution against a real database (
psql,mysql,sqlcmd,sqlite3,mongo, cloud SQL consoles, JDBC clients,\copy). - ORM operations that translate to SQL writes —
INSERT,UPDATE,DELETE,MERGE,UPSERT,BULK INSERT,COPY FROM. - Schema operations —
CREATE,ALTER,DROP,TRUNCATE,RENAME,GRANT,REVOKE. - Migration commands —
alembic upgrade,prisma migrate,django migrate,rake db:migrate,knex migrate:latest,flyway migrate,liquibase update,goose up,dbmate up,sqlx migrate run. - Anywhere a query string is being built — raw SQL files,
cursor.execute,db.query,Sequelize.query,EntityManager.createNativeQuery, template literals tagged as `sql``. - Bulk data operations against any environment named
prod,production,live,customer, or sharing a connection string with one.
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 · 414 lines · 75 tokens per session scan A 61e696e0ba44
database-safety is a skill published in the GitHub repository catpilotai/catpilot-ai-guardrails (2 stars, last pushed 2mo ago), licensed MIT. It adds 75 tokens to every session and 3,748 once invoked, about $0.0004 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 2026-08-31.
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