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Db

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galiprandi
db

Safe Postgres CLI. Reads DATABASE_URL from .env, runs SQL, prints JSON. Read-only by default.

Overview

Publishergaliprandi
Repositoryjob-seeker
Skill namedb
Stars
68
Forks
11
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by galiprandi on GitHub. Read the source before you install it.

Installation

Install the Db AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/galiprandi/job-seeker/tree/main/.agents/skills/db
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/galiprandi/job-seeker.git /tmp/job-seeker
mkdir -p .claude/skills
cp -r /tmp/job-seeker/.agents/skills/db .claude/skills/db
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Db in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Db on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Db is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

db — Postgres CLI for agents

scripts/db.js is the single entry point to the database. Use it instead of psql or inline pg scripts.

Why

  • Reads DATABASE_URL from .env automatically. No manual sourcing, no leaked credentials.
  • Read-only by default. Writes require explicit --write. Prevents accidental destructive SQL.
  • JSON output. Easy to parse, token-efficient.
  • Portable. Works on any machine that cloned the repo and ran onboarding (no psql in PATH required).
  • Never prints the connection string. --ping shows masked user@host/db only.

Commands

bash
# Read (default, JSON array out)
node scripts/db.js "SELECT * FROM users WHERE id = <user_id>"
node scripts/db.js "SELECT data->'profile' AS profile FROM users WHERE id = <user_id>"

# Write (requires --write)
node scripts/db.js "INSERT INTO applications (user_id, platform, company, role, url, status, data) VALUES (<user_id>, 'linkedin', 'Acme', 'Eng Manager', 'https://...', 'applied', '{}'::jsonb)" --write
node scripts/db.js "UPDATE users SET data = jsonb_set(data, '{linkedin_profile}', '\"https://...\"') WHERE id = <user_id>" --write

# Introspection
node scripts/db.js --tables
node scripts/db.js --schema applications
node scripts/db.js --ping

Rules

  • Always use this CLI for DB access. Never write inline pg scripts in skills, never call psql directly.
  • Read-only by default. A statement that does not start with SELECT/WITH/SHOW/EXPLAIN/VALUES/DESCRIBE is refused without --write.
  • Output is JSON. SELECTs print [{...}, ...]. Writes print {rowCount, command}.
  • Never echo DATABASE_URL. If you need to confirm connectivity, use --ping (masked).
  • Parametrize when needed by interpolating safely into the SQL string. This CLI has no parameter binding for CLI args; for user-supplied strings, escape single quotes (' -> '').
  • JSONB access: use data->'key' (jsonb) or data->>'key' (text). Use jsonb_set for updates.

Schema reference

Tables live in public. Discover with --tables and --schema <table>. Known tables:

  • users — single row (repo owner). data JSONB holds profile, job_preferences, style_profile, platforms, linkedin_profile.
  • applications — user_id, platform, company, role, url, status, applied_at, data.
  • messages — recruiter / contact messages.

applications table

Columns: id, user_id, platform, company, role, url, status, applied_at, data

Platforms used:

  • linkedin = Easy Apply jobs
  • linkedin_invite = connection requests
  • email = direct emails to recruiters
  • teamtailor = applications via Teamtailor (with LinkedIn auth, email verification, Connect)
  • humand = applications via Humand.co
  • <company>_career_site, etc. = specific career sites

Status values (pipeline stages, canonical):

Active stages (left to right in the kanban):

  • discovered = found but no action taken
  • contacted = invite/email sent, no formal application
  • applied = application submitted
  • in_review = company reviewing, no response
  • screening = screening call scheduled/done
  • interview = technical interview in progress
  • offer = offer received, negotiating
  • hired = accepted, starting

Closed stages (shown with --closed):

  • rejected = company rejected
  • withdrawn = user withdrew
  • skipped = decided not to apply / not a fit

data JSONB: include source, match (high/medium/low), location, tech array, stage_history array (audit trail of status changes), and any relevant metadata.

Helper library

lib/browser-helpers.js provides atomic helpers that prevent session death between browser calls:

js
const {
  goto, evalJS, evalJSON, clickByText,
  waitFor, waitForSelector, waitForText,
  snapshotReliable, dismissModals,
  dbQuery, dbWrite,
  // Atomic helpers (prevent session death between calls)
  openAndEval, openAndEvalJSON,
  gotoAndEval, gotoAndEvalJSON,
} = require('./lib/browser-helpers');

Atomic helpers chain open/goto + eval in a single shell command to prevent session death between calls:

js
// Open browser + extract in one call (no session death risk)
const jobs = openAndEvalJSON(
  'https://www.linkedin.com/jobs/search/?keywords=...',
  `(function(){ ... return JSON.stringify(...); })()`,
  { session: 'my-session', headed: true }
);

// Navigate + extract in one call (browser already open)
const emails = gotoAndEvalJSON(
  'https://mail.google.com/mail/u/0/#all',
  `(function(){ ... return JSON.stringify(...); })()`,
  { session: 'my-session' }
);

Dependencies

  • Depends on onboarding (.env + DB must exist).
  • Consumed by every flow that reads or writes DB: profile, apply, news, daily.

Frequently asked questions

What does the Db AI skill do?

Safe Postgres CLI. Reads DATABASE_URL from .env, runs SQL, prints JSON. Read-only by default.

Why use Db on TypingMind?

Because you install it once and use it with any model. Db is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Db in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/galiprandi/job-seeker/tree/main/.agents/skills/db. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Db?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Db?

As many as you like. As long as a model supports skills, you can use Db with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Db AI skill free?

Yes. It is published on GitHub by galiprandi under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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