angora-data

angora-data is a skill for Claude Code from Aysnc-Labs/angora. It costs 145 tokens per session (714 once invoked), scanned A, original, MIT.

A small SQLite database helper for inspecting tables, adding one column, inserting a few test rows, or running read-only queries. SQLite is a database stored in a file, and Drizzle is the tool used here to describe and update its tables.

In plain words
What is it for?
Use it to inspect the database structure, add a column through a Drizzle migration, seed 2–5 sample records, or check data with a read-only SELECT or COUNT query.
Why use it?
It removes the need to remember the project's database files, schema locations, migration steps, and query syntax for simple data tasks.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Good fit Use it to inspect the database structure, add a column through a…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aysnc-labs/angora/angora-data
Install

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.

Any agent
npx skills add Aysnc-Labs/angora --skill angora-data
Clone the repo
git clone --depth 1 https://github.com/Aysnc-Labs/angora

Made for: Claude Code.

Wrote 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.

agentmods badge for angora-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/aysnc-labs/angora/angora-data.svg)](https://agentmods.dev/skills/aysnc-labs/angora/angora-data)
Your own site
<a href="https://agentmods.dev/skills/aysnc-labs/angora/angora-data"><img src="https://agentmods.dev/badge/skills/aysnc-labs/angora/angora-data.svg" alt="Measured on agentmods" height="20"></a>
Per session 145 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 714 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00145 $0.00714
Opus 5 $0.00072 $0.00357
Sonnet 5 $0.00029 $0.00143
Haiku 4.5 $0.00015 $0.00071

Measured 7d ago against content hash 826cbb44500a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

angora-data 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 7d 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.

.claude/skills/angora-data/SKILL.md · 75 lines

What it actually says

Data: $ARGUMENTS

Quick operations on the SQLite content layer (src/data/data.sqlite).

Commands

Command Action
schema (or no arguments) Show full database schema (glob src/data/schema/tables/*.ts)
add column <table> <column> Add a column to the Drizzle schema, generate and apply migration (confirm first)
seed <table> Generate 2-5 realistic sample rows
query <description> Run a read-only query and display results

Schema inspection

Glob src/data/schema/tables/*.ts to discover tables, then read individual files for column details. No need to query the database for structure.

Read-only queries

node -e "
  import db from './src/data/db.ts';
  import { media } from './src/data/schema/tables/media.ts';
  const rows = db.select().from(media).all();
  console.table(rows);
"

Use Drizzle's typed API. Import the relevant table from schema/tables/<table>.ts and use db.select(), .where(), etc.

Schema changes (ALTER TABLE, etc.)

All DDL goes through the Drizzle workflow:

  1. Edit the table's file in src/data/schema/tables/ — add the column to the table definition
  2. Generate migrationpnpm db:generate
  3. Apply migrationpnpm db:migrate

Each step requires user approval.

Seeding data

node -e "
  import db from './src/data/db.ts';
  import { <table> } from './src/data/schema/tables/<table>.ts';
  db.insert(<table>).values([
    { /* row 1 */ },
    { /* row 2 */ },
  ]).run();
  console.log('Seeded.');
"

Rules

  • All schema changes require user approval before executing.
  • Foreign keys are ON — respect referential integrity.
  • Use text() for dates (ISO 8601 format).
  • Use integer() for booleans (0/1).
  • query runs read-only — refuse writes via this command.

For heavier work

This skill is for quick operations. For more involved work, use /angora:

  • Schema design (new tables, relational modeling, SEO fields) → /angora-schema
  • Data import (CSV, JSON from inbox) → /angora-import
  • Media processing (images from inbox) → /angora-media
Files

What ships with it

1 file 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.

Changes

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.

  1. 7d ago First seen · 75 lines · 145 tokens per session scan A 826cbb44500a

Subscribe to this mod's changes

angora-data is a skill published in the GitHub repository Aysnc-Labs/angora (6 stars, last pushed 4mo ago), licensed MIT. It adds 145 tokens to every session and 714 once invoked, about $0.0007 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.

Related

Other skills, from other repositories

chrome-ext-storage

This skill should be used when working with data storage in Chrome extensions or when the user asks about extension storage patterns. Trigger when: "chrome.storage", "extension storage", "storage.local", "storage.sync", "storage.session", "IndexedDB in extension", "extension data persistence", "write-through cache"…

RadOrigin-LLC/RAD-Claude-Skills · 106 tokens

architecting-data

Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs…

ancoleman/ai-design-components · 81 tokens

optimizing-sql

Optimize SQL query performance through EXPLAIN analysis, indexing strategies, and query rewriting for PostgreSQL, MySQL, and SQL Server. Use when debugging slow queries, analyzing execution plans, or improving database performance.

ancoleman/ai-design-components · 47 tokens

planning-disaster-recovery

Design and implement disaster recovery strategies with RTO/RPO planning, database backups, Kubernetes DR, cross-region replication, and chaos engineering testing. Use when implementing backup systems, configuring point-in-time recovery, setting up multi-region failover, or validating DR procedures.

ancoleman/ai-design-components · 58 tokens

using-graph-databases

Graph database implementation for relationship-heavy data models. Use when building social networks, recommendation engines, knowledge graphs, or fraud detection. Covers Neo4j (primary), ArangoDB, Amazon Neptune, Cypher query patterns, and graph data modeling.

ancoleman/ai-design-components · 56 tokens

using-relational-databases

Relational database implementation across Python, Rust, Go, and TypeScript. Use when building CRUD applications, transactional systems, or structured data storage. Covers PostgreSQL (primary), MySQL, SQLite, ORMs (SQLAlchemy, Prisma, SeaORM, GORM), query builders (Drizzle, sqlc, SQLx), migrations, connection pooling…

ancoleman/ai-design-components · 92 tokens