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-importgit 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-import)<a href="https://agentmods.dev/skills/aysnc-labs/angora/angora-import"><img src="https://agentmods.dev/badge/skills/aysnc-labs/angora/angora-import/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-import"><img src="https://agentmods.dev/badge/skills/aysnc-labs/angora/angora-import.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 | $0.00142 | $0.00765 |
| Opus 5.5 | $0.00057 | $0.00306 |
| Sonnet 5.5 | $0.00028 | $0.00153 |
| Haiku 4.5 | $0.00014 | $0.00076 |
Grade A, and why
angora-import 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Import: $ARGUMENTS
Import structured data from inbox/ into the SQLite database.
Before you start
- Check inbox — verify the target file exists in
inbox/. - Read schema — glob
src/data/schema/tables/*.tsto discover tables, read relevant files for column details.
Workflow
1. Read and detect format
Read the inbox file. Detect format:
- JSON array —
[{...}, {...}] - Nested JSON —
{ "testimonials": [...], "authors": [...] } - CSV — comma-separated with header row
2. Analysis phase
Map data fields to schema columns. Flag:
- Fields in data without matching columns
- Required columns (NOT NULL, no default) without data
- Type mismatches (string in INTEGER column, etc.)
- Missing foreign key targets (e.g.,
media_idreferencing non-existent media) - Duplicate slugs
- Which table(s) the data maps to
3. Flag schema gaps
If the data has fields that don't match the schema, do NOT modify the schema. Report clearly:
"The data has a
companyfield but the testimonials table doesn't have acompanycolumn. This needs schema work first. Run/angora-schemato update the schema."
4. Present mapping for approval
Show the user:
- Source field → Target column mapping
- Sample of first 2-3 rows as they would be inserted
- Any transformations needed (date format, slug generation, etc.)
- Row count
Wait for user approval before inserting.
5. Import with transactions
node -e "
import db from './src/data/db.ts';
import { <table> } from './src/data/schema/tables/<table>.ts';
const rows = <data>;
db.insert(<table>).values(rows).run();
console.log('Inserted ' + rows.length + ' rows.');
"
Drizzle wraps multi-row inserts in a transaction by default.
6. Verify
Query and show a sample of inserted data:
node -e "
import db from './src/data/db.ts';
import { <table> } from './src/data/schema/tables/<table>.ts';
import { desc } from 'drizzle-orm';
const rows = db.select().from(<table>).orderBy(desc(<table>.id)).limit(5).all();
console.table(rows);
"
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 · 85 lines · 142 tokens per session scan A 75eecf120b1b
angora-import is a skill published in the GitHub repository Aysnc-Labs/angora (6 stars, last pushed 6mo ago), licensed MIT. It adds 142 tokens to every session and 765 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-import compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| angora-importAysnc-Labs/angora | Skill | 6 | 6mo ago | MIT | A | 142 | 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 |