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video_frame_extract

Extract hidden data embedded in video frames by collecting least significant bits and assembling them into a readable byte stream with hex and text preview.

Instructions

Extract LSB data from video frames as bytes. Collects the least significant bit from each byte of the specified frames and assembles them into a byte stream with hex dump and text preview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
framesNoComma-separated frame indices to extract from (default: '0')
file_pathYesPath to AVI video file
max_bytesNoMaximum bytes to extract (default: 4096)
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full weight for behavioral disclosure. It describes the extraction process (collecting LSBs from each byte, assembling into a stream) and output format (hex dump, text preview). However, it omits details like error handling (e.g., out-of-bounds frames), performance implications, whether the file is modified (likely no), or any required codec support.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (two sentences), front-loaded with the main action, and includes essential details about the output. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description should compensate by explaining the return structure. It mentions 'byte stream with hex dump and text preview' but does not specify how these are presented (e.g., JSON object keys, data types). This leaves the agent without clear guidance on consuming the tool's output. Given moderate tool complexity, more detail is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description mentions 'specified frames' but does not add new semantics beyond the schema's parameter descriptions (e.g., format of 'frames' as comma-separated, defaults). It does explain how parameters are used in the overall process, but that aligns with the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Extract LSB data from video frames as bytes') and the resource ('video frames'), with a specific technique (LSB). It explains the process and output (byte stream with hex dump and text preview). However, it does not distinguish from the sibling tool 'video_frame_lsb', which might be a detection variant, so not a perfect 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives like 'video_frame_lsb' or 'video_detect'. There are no prerequisites, exclusions, or usage contexts mentioned. The description is purely functional.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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