Sqlite Data
CheckedHelps with SQLite, data as part of working with databases and data persistence workflows.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add johnrogers/claude-swift-engineering --skill sqlite-data -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
johnrogers
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned johnrogers/claude-swift-engineering at 1dc2cf4d02.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 1dc2cf4d02
- Scanned
- 14 files, 2,714 lines
About this skill
What it does
This skill enables AI agents to interact directly with SQLite databases, allowing for the execution of SQL queries and management of database schemas. It facilitates seamless data retrieval, insertion, updates, and deletion within lightweight, file-based database environments.
When to use it
- You need to query small datasets stored locally without setting up a full server environment.
- Your workflow requires rapid prototyping where a persistent but portable database is essential.
- You are building tools that must analyze structured data embedded in application files or logs.
- You require low-latency read/write access for agents operating in constrained resource settings.
Key capabilities
- Execute standard SQL commands (SELECT, INSERT, UPDATE, DELETE) against SQLite instances.
- Manage database connections and handle schema definitions dynamically.
- Process results returned from complex queries for immediate agent reasoning.
- Support for file-based database storage accessible by the agent's execution context.
Example prompts
- "Create a SQLite table named 'users' with columns for id, name, and email, then insert three sample records."
- "Query the latest five transactions from my local SQLite database and summarize the total amount spent."
- "Update all active user statuses to 'inactive' in the current database file based on their last login date."
Tips & gotchas
Ensure the target SQLite database file is accessible within the agent's working directory or explicitly mounted before attempting connections. While powerful for local tasks, this skill does not support remote database hosts or cloud-managed SQL services without additional infrastructure setup.