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 agentmods add skills/aws-samples/sample-okf-llm-wiki/setupnpx skills add aws-samples/sample-okf-llm-wiki --skill setupgit clone --depth 1 https://github.com/aws-samples/sample-okf-llm-wikiWhat 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 | $0.00060 | $0.00651 |
| Opus 5 | $0.00030 | $0.00326 |
| Sonnet 5 | $0.00012 | $0.00130 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade B, and why
setup scanned grade B with 1 finding 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 3d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
mkdir -p ~/.okf && chmod 700 ~/.okf The source is not reproduced here
Licensed MIT-0
The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 3d ago First seen · 79 lines · 60 tokens per session scan B e84d4bc219aa
setup is a skill published in the GitHub repository aws-samples/sample-okf-llm-wiki (23 stars, last pushed 4d ago), licensed MIT-0. It adds 60 tokens to every session and 651 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
okf-enrich
Guidance for an AI agent to enrich an Open Knowledge Format (OKF) bundle with high-quality concept descriptions using its own LLM — grounded in the bundle's schema, data profile, and samples — then optionally sync them back to the source. Use when an OKF bundle has missing, weak, or low-quality descriptions that…
okf-producer-generator
Guidance and the bundled OKF specification for building a new Open Knowledge Format (OKF) producer/connector skill in this project — the architectural principles, the okf-go library contract, the produce/ingest/schema command surface, the secret-handling and sync conventions, and the exact registration steps. Use when…
okf-bigquery
Google Cloud BigQuery connector that produces and ingests Open Knowledge Format (OKF) bundles from dataset schemas, table/field descriptions, and metadata. Use when documenting or cataloging BigQuery datasets, extracting schema metadata into OKF, or syncing descriptions back to BigQuery tables and fields.
okf-csv
CSV connector that produces and ingests Open Knowledge Format (OKF) bundles from a directory of CSV files. Infers each file's column schema (integer/number/boolean/date/string) by sampling rows, optionally embeds a per-column data profile and sample rows, and syncs descriptions back to a .okf-metadata.yaml sidecar.…
okf-mongodb
MongoDB connector that produces and ingests Open Knowledge Format (OKF) bundles by sampling documents to infer each collection's schema. Emits one concept per collection with a Name | Type | Presence table (top-level fields, with mixed types shown as a union and presence as the percentage of sampled documents). The…
okf-mysql
MySQL connector that produces and ingests Open Knowledge Format (OKF) bundles from database schemas and table/column comments. Use when documenting or cataloging a MySQL database, extracting its schema and comments into OKF, or syncing descriptions back to MySQL via DDL.