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Blip 2 Vision Language

Checked
davila7·vlatest·video-media·MIT

This skill uses Blip 2's image understanding to generate detailed captions and descriptions from images, boosting accessibility and content creation.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add davila7/claude-code-templates --skill blip-2-vision-language -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

davila7

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned davila7/claude-code-templates at 79182c51fb.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
79182c51fb
Manifest
cli-tool/components/skills/ai-research/multimodal-blip-2/SKILL.md
Scanned
3 files, 1,667 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The blip-2-vision-language skill integrates the BLIP-2 model to enable AI agents to perform advanced visual question answering and image captioning tasks. It allows agents to interpret complex visual data by combining a vision encoder with a large language model for precise, context-aware responses.

When to use it

  • Analyze screenshots of software interfaces to identify UI elements or diagnose errors visually.
  • Interpret diagrams, charts, or scientific illustrations to extract trends and explain underlying concepts.
  • Generate descriptive captions for uploaded images to assist in accessibility or content tagging workflows.
  • Solve visual puzzles or logic problems presented entirely through graphical representations.

Key capabilities

  • Visual Question Answering: Answers specific questions about the content within an image.
  • Image Captioning: Generates natural language descriptions summarizing the main subjects and actions in a picture.
  • Multimodal Reasoning: Connects visual evidence with textual queries to derive accurate conclusions.

Example prompts

  • "What is the value of the variable highlighted in red in this code screenshot?"
  • "Describe the process flow shown in this diagram step-by-step."
  • "Identify any safety hazards present in this photograph of a construction site."

Tips & gotchas

Ensure images are high-resolution to maximize the model's ability to discern fine details and text. Complex charts with dense data may require simplified prompts to get accurate summaries rather than raw data extraction.