okf-enrich

okf-enrich is a skill for Claude Code, Codex from xSAVIKx/okf-skills. It costs 86 tokens per session (4,125 once invoked), scanned A, original, Apache-2.0.

Guidance for an AI coding agent that improves descriptions in an Open Knowledge Format bundle. It uses the bundle’s structure, data details, and samples as evidence rather than providing a separate AI model.

In plain words
What is it for?
Enriching and documenting OKF concepts, usually after another connector creates the bundle and before descriptions are synced to the source.
Why use it?
It gives the agent a consistent way to write useful documentation for datasets, tables, files, and folders that have missing or weak descriptions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code; mentions Gemini CLI.

Good fit Enriching and documenting OKF concepts, usually after another connector creates the bundle and before descriptions are synced to the source.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xsavikx/okf-skills/okf-enrich
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 xSAVIKx/okf-skills --skill okf-enrich
Clone the repo
git clone --depth 1 https://github.com/xSAVIKx/okf-skills

Made for: Claude Code, Codex.

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 okf-enrich

README.md
[![agentmods](https://agentmods.dev/badge/skills/xsavikx/okf-skills/okf-enrich/github.svg)](https://agentmods.dev/skills/xsavikx/okf-skills/okf-enrich)
Your own site
<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.

agentmods 80×15 button for okf-enrich

Your own site · 80×15
<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>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,125 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00086 $0.04125
Opus 5.5 $0.00034 $0.01650
Sonnet 5.5 $0.00017 $0.00825
Haiku 4.5 $0.00009 $0.00413

Measured 2mo ago against content hash a81c9c433d81, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

skills/okf-enrich/SKILL.md · 223 lines

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 --profile and --sample (the four SQL connectors), and the descriptions you write can be pushed back to the origin with the connector's ingest --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 |
| ...

Read the full file on GitHub · 223 lines

Files

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.

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. 2mo ago First seen · 223 lines · 86 tokens per session scan A a81c9c433d81

Subscribe to this mod's changes

okf-enrich is a skill published in the GitHub repository xSAVIKx/okf-skills (38 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 86 tokens to every session and 4,125 once invoked, about $0.0003 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 2026-08-30.

Related

okf-enrich compared with skills from other repositories

okf-enrich next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
okf-enrichxSAVIKx/okf-skillsSkill381mo agoApache-2.0A86Claude Code, Codex
LLMjjyaoao/HelloAgentsSkill3.4k1mo agononeA59Claude Code, Codex
ASRjjyaoao/HelloAgentsSkill3.4k1mo agononeA65Claude Code, Codex
VLMjjyaoao/HelloAgentsSkill3.4k1mo agononeA56Claude Code, Codex
okfy0dust/OKFySkill742mo agoMITA54Codex
alpha-vantagegauss314/skillsSkill2534mo agoMITA24Claude Code, Codex
macrotrendsgauss314/skillsSkill2534mo agoMITA31Claude Code, Codex