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 xSAVIKx/okf-skills --skill okf-enrichgit clone --depth 1 https://github.com/xSAVIKx/okf-skillsWrote 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/xsavikx/okf-skills/okf-enrich)<a href="https://agentmods.dev/skills/xsavikx/okf-skills/okf-enrich"><img src="https://agentmods.dev/badge/skills/xsavikx/okf-skills/okf-enrich/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/xsavikx/okf-skills/okf-enrich"><img src="https://agentmods.dev/badge/skills/xsavikx/okf-skills/okf-enrich.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00086 | $0.04125 |
| Opus 5 | $0.00043 | $0.02063 |
| Sonnet 5 | $0.00017 | $0.00825 |
| Haiku 4.5 | $0.00009 | $0.00413 |
Grade A, and why
okf-enrich 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 12d 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OKF Bundle Enrichment Guidance Skill
This skill teaches an AI agent (Claude Code, Cursor, Gemini CLI, Copilot, …) how to enrich an Open Knowledge Format (OKF) bundle — adding or improving the human-readable description of each concept (table, dataset, file, directory) — using the agent's own LLM.
There is deliberately no binary and no embedded model here. Generating a good description is a judgment task, and the harness driving the project already has a capable LLM in the loop. Embedding a second one would mean a model calling a tool that calls another model: redundant cost, an extra API key to manage, and usually a worse result than the model already doing the work. So enrichment is delivered as guidance — the procedure and the quality bar — for whatever LLM is present, exactly as okf-reader is guidance for reading a bundle.
When to Use
Load this skill when asked to enrich, document, describe, annotate, or "improve the descriptions in" an OKF bundle — typically after a connector has produced the bundle and before syncing descriptions back to the source.
Pairs with:
okf-reader— follow its rules to read and navigate the bundle efficiently (index-first, frontmatter-only when possible, grep for targeted lookups).- the connectors (
okf-sqlite,okf-mysql,okf-postgresql,okf-bigquery,okf-fs,okf-git) — the producers and the sync target. Enrichment is far better when the bundle was produced with--profileand--sample(the four SQL connectors), and the descriptions you write can be pushed back to the origin with the connector'singest --sync.
The OKF concept document
Each concept is a markdown file with YAML frontmatter:
---
type: SQLite Table
title: orders
description: # <- the field you write
resource: sqlite:///.../orders
tags: [sqlite, table]
timestamp: 2026-06-13T12:00:00Z
---
# Columns
| Name | Type | Primary Key | Nullable | Default |
| --- | --- | --- | --- | --- |
## Data Profile # present only when produced with --profile
| Column | Non-Null | Null | Distinct | Min | Max |
| --- | --- | --- | --- | --- | --- |
## Sample # present only when produced with --sample
| id | customer_id | total | status |
| ...
What ships with it
7 files 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.
- 12d ago First seen · 223 lines · 86 tokens per session scan A a81c9c433d81
okf-enrich is a skill published in the GitHub repository xSAVIKx/okf-skills (33 stars, last pushed 12d ago), licensed Apache-2.0. It adds 86 tokens to every session and 4,125 once invoked, about $0.0004 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 2026-08-30.
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