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 Aysnc-Labs/angora --skill angora-datagit clone --depth 1 https://github.com/Aysnc-Labs/angoraWrote 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/aysnc-labs/angora/angora-data)<a href="https://agentmods.dev/skills/aysnc-labs/angora/angora-data"><img src="https://agentmods.dev/badge/skills/aysnc-labs/angora/angora-data/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/aysnc-labs/angora/angora-data"><img src="https://agentmods.dev/badge/skills/aysnc-labs/angora/angora-data.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 | $0.00145 | $0.00714 |
| Opus 5.5 | $0.00058 | $0.00286 |
| Sonnet 5.5 | $0.00029 | $0.00143 |
| Haiku 4.5 | $0.00015 | $0.00071 |
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 2mo 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.
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:
- Edit the table's file in
src/data/schema/tables/— add the column to the table definition - Generate migration —
pnpm db:generate - Apply migration —
pnpm 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). queryruns 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
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.
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.
- 2mo ago First seen · 75 lines · 145 tokens per session scan A 826cbb44500a
angora-data is a skill published in the GitHub repository Aysnc-Labs/angora (6 stars, last pushed 6mo ago), licensed MIT. It adds 145 tokens to every session and 714 once invoked, about $0.0006 per session on Opus 5.5. 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.
angora-data compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| angora-dataAysnc-Labs/angora | Skill | 6 | 6mo ago | MIT | A | 145 | Claude Code |
| architecting-dataancoleman/ai-design-components | Skill | 527 | 11mo ago | MIT | A | 81 | Claude Code |
| using-graph-databasesancoleman/ai-design-components | Skill | 527 | 11mo ago | MIT | A | 56 | Claude Code |
| optimizing-sqlancoleman/ai-design-components | Skill | 527 | 11mo ago | MIT | A | 47 | Claude Code |
| planning-disaster-recoveryancoleman/ai-design-components | Skill | 527 | 11mo ago | MIT | A | 58 | Claude Code |
| using-relational-databasesancoleman/ai-design-components | Skill | 527 | 11mo ago | MIT | A | 92 | Claude Code |
| ingesting-dataancoleman/ai-design-components | Skill | 527 | 11mo ago | MIT | A | 53 | Claude Code |