context-okf-llm-ingest

context-okf-llm-ingest is a skill for Claude Code, Codex from kerbelp/metatron. It costs 45 tokens per session (1,566 once invoked), scanned A, original, MIT.

A skill for having an AI agent extract a codebase’s implementation decisions into OKF, a plain Markdown format for recording project rules and choices. The files can be reviewed by people before becoming the project’s official decisions.

In plain words
What is it for?
Use it to inspect a repository, write candidate decision files locally, review them in Git, and import approved files into Metatron, the project-context system.
Why use it?
It lets teams document conventions, rejected approaches, and edge cases without relying on a built-in importer or an API key, while keeping final approval with a person.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to inspect a repository, write candidate decision files locally, review them in Git, and import approved files into Metatron, the project-context system.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kerbelp/metatron/context-okf-llm-ingest
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 kerbelp/metatron --skill context-okf-llm-ingest
Clone the repo
git clone --depth 1 https://github.com/kerbelp/metatron

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 context-okf-llm-ingest

README.md
[![agentmods](https://agentmods.dev/badge/skills/kerbelp/metatron/context-okf-llm-ingest/github.svg)](https://agentmods.dev/skills/kerbelp/metatron/context-okf-llm-ingest)
Your own site
<a href="https://agentmods.dev/skills/kerbelp/metatron/context-okf-llm-ingest"><img src="https://agentmods.dev/badge/skills/kerbelp/metatron/context-okf-llm-ingest/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 context-okf-llm-ingest

Your own site · 80×15
<a href="https://agentmods.dev/skills/kerbelp/metatron/context-okf-llm-ingest"><img src="https://agentmods.dev/badge/skills/kerbelp/metatron/context-okf-llm-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,566 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 $0.00045 $0.01566
Opus 5.5 $0.00018 $0.00626
Sonnet 5.5 $0.00009 $0.00313
Haiku 4.5 $0.00005 $0.00157

Measured 27d ago against content hash a565e5763920, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

context-okf-llm-ingest 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 27d 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.

.roo/skills/context-okf-llm-ingest/SKILL.md · 136 lines

How it starts

The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Authoring repository decisions with an LLM

Overview

Capture a codebase's real implementation decisions — preferred patterns, rejected approaches, edge cases, internal conventions — as structured OKF markdown files. Any coding agent can author them; metatron ingest is not required.

In files-first mode, agents read the Git-tracked files directly. No database, MCP server, or import is needed. The files are a portable Open Knowledge Format (OKF) v0.1 bundle and implement the Repository Context Layer.

Human review is the canonical boundary. Follow the repository's configured review gate: either a human-reviewed PR containing decision files, or separate review of staged candidates. Authoring on a branch is not permission to merge.

Directory name: context/ is the default knowledge-base directory. Honor the configured context_dir in metatron.toml or METATRON_CONTEXT_DIR; pre-rename repos may still use metatron/. Substitute the resolved directory in all paths and commands below. In monorepos use the knowledge base nearest the code, such as apps/web/context/, and the workspace's installed skills.

Workflow (files-first)

  1. Read the repository instructions, context.md, and relevant existing decisions before exploring implementation details. Check the review gate below.
  2. Inspect source and tests. Extract prescriptive, non-obvious conventions supported by that evidence, rather than generic framework advice.
  3. Write one OKF file per new convention in the gate's destination directory. Amend an existing decision when it already covers the same convention.
  4. Validate the destination with metatron files lint --path context/decisions for the PR gate, or metatron files lint --path context/candidate for staging.
  5. Inspect git status --short and the complete diff. New untracked files need their own view, e.g. git diff --no-index -- /dev/null context/decisions/repo-pattern-for-stores.md (exit 1 means differences). Include the decision changes in the human-reviewed PR, or present the staged candidates for human selection. Stop before merging or promoting anything without the required human review.

Read the full file on GitHub · 136 lines

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. 27d ago Changed · -58 lines · -8 tokens per session a565e5763920
  2. 1mo ago First seen · 194 lines · 53 tokens per session scan A 80d9058adee5

Subscribe to this mod's changes

context-okf-llm-ingest is a skill published in the GitHub repository kerbelp/metatron (27 stars, last pushed 2d ago), licensed MIT. It adds 45 tokens to every session and 1,566 once invoked, about $0.0002 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.