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

Beyond the readOnly/openWorld annotations, the description discloses the return payload (preview, downloadable file, size, duration, author + link), the licensing terms (free for commercial use, no on-screen credit required), and two hard operating constraints: always show credit to the user, and download into the project rather than hot-linking. This is exactly the behavioral context annotations cannot carry.

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

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

Purpose is front-loaded in the first clause, and the remaining sentences each carry distinct payload: return contents, the credit/selection workflow, licensing, and query-writing rules. It is dense but not padded; only the licensing sentence lightly overlaps the credit instruction.

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

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

With no output schema and five parameters, the description compensates fully by enumerating what results contain and by spelling out the human-in-the-loop step before download. An agent has everything needed to call it and to act correctly on the results.

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

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

Schema description coverage is 100%, so the baseline is 3. The description still adds real meaning: 'search in English for the most results' refines the language parameter's intent, and the 'describe the shot, not the idea' rule with a worked example ('woman looking surprised at phone') materially improves how the query parameter should be filled.

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

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

The description states a specific verb and resource with its source: 'Search free stock footage and photos (Pixabay).' It also frames the job ('for a video or post the user asked for'), which separates it informally from library tools like list_library_media. It stops short of naming a sibling alternative explicitly, so it is clear but not maximally differentiated.

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

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

Strong contextual triggers are given ('b-roll for an edit, a clip or image for a reel beat, a background') plus a concrete workflow: show options with credit, let the user choose, then download. It lacks an explicit 'use X instead when...' routing against generate_image or list_library_media, which keeps it short of a 5.

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