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/awslabs/mcp/amazon-aurora-dsql-skillnpx skills add awslabs/mcp --skill amazon-aurora-dsql-skillgit clone --depth 1 https://github.com/awslabs/mcpWhat 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 | $0.00199 | $0.05108 |
| Opus 5 | $0.00100 | $0.02554 |
| Sonnet 5 | $0.00040 | $0.01022 |
| Haiku 4.5 | $0.00020 | $0.00511 |
Grade A, and why
amazon aurora dsql 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 yesterday.
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.
Copies of this mod
5 near-identical copies found in the catalogue:
- aurora dsql — 100% identical, 2 lines differ
- dsql — 100% identical, 2 lines differ
- aws dsql — 98% identical, 2 lines differ
- distributed postgres — 98% identical, 2 lines differ
- distributed sql — 98% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Aurora DSQL Skill
Aurora DSQL is a serverless, PostgreSQL-compatible distributed SQL database. This skill provides direct database interaction via MCP tools, schema management, migration support, and multi-tenant patterns.
Key capabilities:
- Direct query execution via MCP tools
- Schema management with DSQL constraints
- Migration support and safe schema evolution
- Multi-tenant isolation patterns
- IAM-based authentication
Reference Files
Load these files as needed for detailed guidance:
development-guide.md
When: ALWAYS load before implementing schema changes or database operations Contains: Best Practices, DDL rules, connection patterns, transaction limits, data type serialization patterns, application-layer referential integrity instructions, security best practices
MCP:
mcp-setup.md
When: Always load for guidance using or updating the DSQL MCP server Contains: Instructions for setting up the DSQL MCP server with 2 configuration options as sampled in mcp/.mcp.json
- Documentation-Tools Only
- Database Operations (requires a cluster endpoint)
mcp-tools.md
When: Load when you need detailed MCP tool syntax and examples. PREFER MCP tools for ad-hoc queries — execute directly rather than writing scripts. Contains: Tool parameters, detailed examples, usage patterns, input validation
language.md
When: MUST load when making language-specific implementation choices. ALWAYS prefer DSQL Connector when available. Contains: Driver selection, framework patterns, connection code for Python/JS/Go/Java/Rust
dsql-examples.md
When: Load when looking for specific implementation examples Contains: Code examples, repository patterns, multi-tenant implementations
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 342 lines · 199 tokens per session scan A d5f335b20864
amazon aurora dsql is a skill published in the GitHub repository awslabs/mcp (9,644 stars, last pushed 4d ago), licensed Apache-2.0. It adds 199 tokens to every session and 5,108 once invoked, about $0.0010 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.
Other skills, from other repositories
code_explorer
Explores the repository to locate primary source files, coupled UI components, and test files for bug reports or feature requests.
quality
Evaluates whether a GitHub issue is spam, empty, needs more information, or is OK to proceed.
prowler-ui
Prowler UI-specific patterns. For generic patterns, see: typescript, react-19, nextjs-16, tailwind-4. Trigger: When working inside ui/ on Prowler-specific conventions (shadcn, folder placement, actions/adapters, shared types/hooks/lib).
prowler-test-api
Testing patterns for Prowler API: JSON:API, Celery tasks, RLS isolation, RBAC. Trigger: When writing tests for api/ (JSON:API requests/assertions, cross-tenant isolation, RBAC, Celery tasks, viewsets/serializers).
prowler-pr
Creates Pull Requests for Prowler following the project template and conventions. Trigger: When working on pull request requirements or creation (PR template sections, PR title Conventional Commits check, changelog gate/no-changelog label), or when inspecting PR-related GitHub workflows like conventional-commit.yml…
prowler
Main entry point for Prowler development - quick reference for all components. Trigger: General Prowler development questions, project overview, component navigation (NOT PR CI gates or GitHub Actions workflows).