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OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs.
Passed 22 of 23 test cases with the skill, and 11 of 23 without it.
and 10 more in the full report
11 fixed11 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
How many parameters does the `RN50` backbone model in OpenAI CLIP contain?
| Checked | Without skill | With skill |
|---|---|---|
| The response states `RN50` has approximately 102M parameters. | Missed | Passed |
The instructions your model reads when the skill loads.
This skill is repo-local and stays inactive until explicitly activated.
When the original instructions refer to legacy tool names, use these Kheish mappings:
terminal => bashweb_extract => web_fetch, plus web_search when discovery is neededsearch_files => grep_search and glob_searchbrowser_* tools require a browser-capable surfaced tool or MCP; if none is available, use the closest available surface and say so explicitlyWhen the instructions mention local helper files, resolve them from ${KHEISH_SKILL_DIR}.
OpenAI's model that understands images from natural language.
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Metrics:
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test cases passed, vs 11 / 23 without
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