vidshaper

by gulkoa

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

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Latest release: v1.2.1
Disambiguation5/5
Each tool targets a distinct video editing operation—audio removal vs. extraction, resizing vs. cropping, overlays vs. filters—so there is no real ambiguity. The descriptions further clarify any potential overlap, such as adjust_volume vs. normalize_audio.
Naming Consistency4/5
The vast majority of tool names follow a clear verb_noun pattern (remove_audio, trim_video, detect_scenes). Two exceptions—picture_in_picture and video_from_images—are noun phrases, breaking the otherwise consistent scheme.
Tool Count2/5
At 31 tools, this is a hefty surface that exceeds the comfortable 16-25 tool range. While the scope of video editing is broad and each tool serves a purpose, the sheer count makes the server feel dense and harder to navigate.
Completeness5/5
The tool set covers the full video editing lifecycle: capture (get_video_info, sample_frames), cutting (trim, concat), transformation (resize, crop, rotate), audio handling (extract, replace, normalize), overlays (text, watermark, box, blur), and more. Missing advanced features like stabilization or chroma keying, but the core domain is thoroughly covered.
Average 3.9/5 across 31 of 31 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- Last stable release on August 4, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions re-encoding and quality affects file size, but does not disclose critical behaviors: what happens if output_path is omitted, whether existing files are overwritten, whether the source is modified, or what the tool returns upon success/failure. This is a significant gap for a mutation tool.
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 a single, front-loaded sentence that states the action, target formats, and quality setting with no wasted words. It earns every word and is easy to scan.
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?
For a tool that re-encodes files, this description is incomplete. It lacks explanation of output path default behavior, overwrite policy, return values, or possible errors. With no output schema and no annotations, the description should cover these operational details, but it covers only the basic purpose and quality.
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 description coverage is 100%, so the baseline is 3. The description adds minor context by naming the format list and quality setting, but the schema already describes each parameter, including the quality/size tradeoff. No additional meaning is given for input_path or output_path beyond their schema descriptions.
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 tool re-encodes videos to specific target formats (mp4, webm, mov, mkv), which distinguishes it from most siblings like trim_video or resize_video. However, it does not explicitly differentiate from compress_video, which also involves re-encoding and could overlap in use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when a video needs to be converted to another container/format, but it provides no explicit guidance on when not to use it or how it compares to alternatives like compress_video. No exclusions or alternative tool references are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does mention the time-range option ('Optionally limited to a time range'), which is a useful behavior, but it omits other important details such as whether the source file is modified, the default output behavior, or how the overlay interacts with existing video content. This is insufficient given the lack of annotations.
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 two short sentences and front-loaded with the core action. Every word serves a purpose, with no redundant information. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema covers all 9 parameters, so the tool is functionally clear. However, the description lacks usage guidelines and behavioral context beyond the time-range option. For a tool with no annotations and no output schema, a score of 3 reflects that it is adequate but has clear gaps in contextual completeness.
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 description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; 'time range' hints at start/end parameters, but those are already fully described in the schema. No extra parameter semantics are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Draw text on the video' and lists example uses (caption, title, label). It distinguishes from siblings like burn_subtitles and add_watermark by focusing on general text overlay rather than subtitle files or image watermarks.
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 on when to use this tool versus alternatives. The description does not mention siblings like add_watermark or burn_subtitles, nor does it specify contexts where a text overlay is preferred. The only hint is the parenthetical 'caption, title, label', but it does not constitute explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The phrase 'pull out' is ambiguous and could be read as removing the audio from the video, especially given the existence of a sibling named remove_audio. The description does not clarify that the original video is left unchanged, nor does it address potential side effects such as overwriting files or supporting source video formats. With no annotations, this ambiguity and lack of behavioral disclosure is a significant gap.
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 a single, front-loaded sentence that states the primary action, then lists the output formats. Every word is purposeful, with no redundancy or filler. It is extremely concise while still being informative.
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?
For a tool with no annotations and no output schema, the description is too sparse. It fails to clarify whether the operation is non-destructive to the source video, especially given the sibling tools remove_audio and replace_audio. It also doesn't mention default behavior when output_path is omitted or whether the original file is preserved. This leaves the agent with insufficient information to use the tool safely and correctly.
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?
The input schema provides descriptions for all 3 parameters, achieving 100% coverage. The tool description adds no extra meaning beyond the schema—the mention of formats (mp3, wav, m4a, flac) is already captured in the format parameter's enum and description. The baseline of 3 applies because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Pull the audio track out of a video') and the result ('into its own file'), listing all supported output formats. This distinguishes it from siblings like remove_audio and replace_audio, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a standalone audio file is needed, but it does not explicitly state when to prefer this tool over siblings like remove_audio or replace_audio. No exclusions or alternative tool names are mentioned, leaving usage guidance to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the parameter meanings from the schema and does not mention output path defaults when output_path is omitted, whether the input is modified, or any return values/prerequisites.
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 a single sentence that immediately states the tool's purpose without any wasted words. It is front-loaded and easy to parse.
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?
The tool is simple, but the description omits critical contextual behavior: output_path is optional in the schema but the description doesn't explain what happens when omitted. It also doesn't clarify behavior when neither degrees nor flip is provided, leaving ambiguity for the agent.
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 description coverage is 100%, so all parameters (input_path, output_path, degrees, flip) are already well-documented with names, types, and enums. The description adds little beyond the schema except the 'clockwise' and 'and/or' combination wording, providing no new semantic meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the exact operation: rotating a video by 90/180/270 degrees clockwise and/or mirroring horizontally or vertically. This clearly distinguishes it from sibling tools like resize_video or crop_video.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for video orientation and mirroring adjustments, but it provides no explicit guidance on when to choose this tool over alternatives or any exclusions. Given the large sibling set, more explicit usage context would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions neutral values and the black & white effect of saturation 0, but fails to state whether the operation writes to an output file, modifies in place, or has any side effects.
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?
A single concise sentence that is front-loaded with the action and resources, followed by a useful parenthetical. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the schema covers parameters well, but the description lacks usage context and output behavior. For a video editing tool with an output_path parameter, mentioning that it writes to a file would improve completeness.
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% with detailed parameter descriptions, so baseline is 3. The description adds minimal extra meaning by explaining neutral values and the black & white interpretation, but this does not significantly elevate understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'tune' and explicitly names the resources (brightness, contrast, saturation). It clearly distinguishes from sibling tools like trim_video or remove_audio by focusing on color adjustments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by naming the adjustable properties and providing neutral values, but does not explicitly state when to use this tool versus alternatives or provide any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It explains that x/y is the top-left corner and that the region is kept, but does not disclose important behavior such as whether output_path is required, how the output file is written, whether audio is preserved, or what happens if the crop boundaries exceed the frame.
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 two concise sentences, front-loaded with the main action and coordinate clarification. There is no redundancy or wasted words.
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?
Despite having 6 parameters and no output schema or annotations, the description only covers the core cropping concept. It omits critical context such as the role of the optional output_path, validation behavior, and what the tool returns or writes, leaving the agent with unanswered questions for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 adds value by clarifying that x/y refers to the top-left corner of the region to keep, which complements the schema's per-parameter descriptions and removes ambiguity about coordinate meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool crops a rectangular region from the video frame, using a specific verb and resource. It also differentiates from sibling tools like resize_video and trim_video by explicitly mentioning the crop region and coordinate origin.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: use this when you need to keep a rectangular portion of the video. However, there is no explicit guidance on when to use this versus alternatives like resize_video or trim_video, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavioral traits. It states the overlay operation and optional parameters, but fails to mention whether the output is written to output_path, whether the original video is overwritten, or any format/codec requirements. The description does not disclose the non-destructive nature (if any) or permissions needed, leaving significant ambiguity.
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 a single, front-loaded sentence that conveys the action, target, and main options without waste. Every word adds value and no redundant details are present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a video-processing tool with no output schema and no annotations, the description should clarify output destination and possible side effects. It covers the core functionality but omits whether the result is written to output_path and does not differentiate from similar tools like burn_subtitles. The presence of complete schema descriptions compensates partially, but the missing output semantics leave a gap.
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 description coverage is 100%, so parameters are individually documented in the schema. The description adds high-level meaning (corner, size, opacity) but does not give format details or default values beyond what the schema provides. This matches the baseline of 3 for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Overlay' with a clear resource ('an image on the video') and includes key modifiers ('chosen corner', 'size and opacity'). This clearly distinguishes it from siblings like add_text_overlay (text overlay) and burn_subtitles (subtitle overlay).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the tool's purpose obvious: adding a logo/watermark to a video. It does not explicitly state when not to use it or name alternatives, but the context is clear enough for an agent to select it for watermarking needs. No exclusions or alternative tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. The word 'Permanently' is a meaningful disclosure that subtitles become part of the video and cannot be removed later. However, it does not state what happens when output_path is omitted (e.g., whether the input is overwritten) or any codec/performance considerations.
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 a single sentence, front-loaded with the core action, and contains no unnecessary words or filler. It is appropriately terse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple and the schema covers all parameters, but the lack of annotations and output schema means the description should compensate. It does not clarify default output behavior or differentiate from add_text_overlay, leaving some ambiguity for an AI agent. Still, it provides a complete high-level understanding for basic use.
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 description coverage is 100% (all four parameters have descriptions). The description text adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('render') and specifies the resource ('subtitle file onto the video frames'), clearly distinguishing it from sibling tools like add_text_overlay. It also defines the subtitle file formats (.srt or .ass).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool (to permanently burn subtitles into video frames) but does not explicitly mention alternatives or exclusions. It does not compare with add_text_overlay or note cases where soft subtitles would be preferable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that it draws on the video and can be time-limited, but does not mention whether the original file is modified, if a new file is written to output_path, or any potential side effects like overwriting. This is a significant gap for a mutation tool with no annotation safety hints.
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 two sentences, front-loaded with the primary action ('Draw a rectangle outline or filled box'), and every word adds value. There is no fluff or repetition of schema fields, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, 100% schema coverage, and no output schema, the description is reasonably complete for selecting the tool, but lacks important operational context like whether it requires output_path, how it interacts with audio or other video properties, or what the visual result looks like beyond a basic rectangle. It is minimal but not fully inadequate for a complex tool.
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?
The schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds minor value by calling out the outline vs. filled box option (which already exists in the 'fill' param) and the time-range limitation (also already in 'start'/'end'). No additional semantic depth beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: drawing a rectangle outline or filled box on a video, with specific use cases of highlighting or redacting a region. This distinguishes it from sibling tools like blur_region, which would redact via blurring, and crop_video, which modifies the frame rather than adding an overlay.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: when the goal is highlighting or redacting a region. However, it does not explicitly mention alternatives or when not to use it, such as 'use blur_region if you need to obscure content without a visible box outline.' This leaves room for ambiguity but gives a solid contextual cue.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing safety-relevant behavior. It only says 'save' and does not disclose whether an existing output file would be overwritten, what happens if output_path is omitted, or any error conditions.
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?
Two concise sentences, front-loaded with the core action and followed by a helpful use-case hint. No wasted words or redundant restating of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema covers parameters well and the tool is simple, but the description does not explain behavior around optional output_path (only input_path is required) or what the tool returns. A small but important gap remains.
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?
The input schema already documents all four parameters with descriptions, including defaults for format and timestamp. The description adds no additional parameter-specific meaning, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Save a single frame of the video as an image') and resource involved. It distinguishes itself from siblings like extract_audio or create_gif by specifying a still image output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides concrete use cases ('Good for previews and cover images'), which gives clear context for when to use it. However, it does not explicitly mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden. It adds a key behavioral fact ('Video is untouched') and explains the loudness standard, but it does not disclose whether the original file is preserved, what the tool returns, or any potential side effects like quality changes. This is acceptable but not comprehensive.
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 two sentences, each earning its place. It starts with the action and outcome, then adds a crucial caveat. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core purpose and a key limitation (video untouched), but with no output schema and no annotations, it should mention what the tool returns and whether the input is modified. The output_path parameter hints at a new file, but the description doesn't explicitly confirm non-destructive behavior or result format. There is room for improvement.
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 description coverage is 100%, so the schema already documents all parameters. The description does not add meaning to input_path or output_path beyond the schema; it only broadly frames the tool's purpose. The baseline of 3 applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Normalize') and resource ('audio') with a concrete outcome ('broadcast-standard loudness (EBU R128)'). It also distinguishes the tool from siblings by noting that video is untouched, which is not obvious from the name alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives some contextual use cases ('podcast/social-media levels', 'fixes too-quiet or wildly varying audio') but does not explicitly mention when to prefer this over sibling tools like adjust_volume, nor does it state exclusions. The guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must shoulder the behavioral burden. It discloses the key behavior (strips audio, leaves silent video) and adds the performance trait of no re-encoding. Missing details include whether the original input is preserved, how multiple audio tracks are handled, or any format limitations, but for a simple operation the core behavior is covered.
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 only two short sentences and gets straight to the point. Every word adds value: it states the action, the result, and a useful performance characteristic. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with two well-documented parameters and no output schema, the description covers the essential behavior and outcome effectively. It falls short only in not mentioning edge cases like multiple audio tracks or confirming the original file is left untouched, but overall it is sufficiently complete for the tool's simplicity.
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% with clear descriptions for input_path and output_path, so the baseline is 3. The description adds no additional parameter-level detail beyond what the schema provides, such as file format requirements or path conventions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Strip') and resource ('the audio track from a video'), and specifies the outcome ('leaving silent video'). It is easily distinguished from sibling tools like extract_audio, which would export the audio separately, and replace_audio, which would swap the track.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The tool's purpose implicitly tells the user when to use it (when silent video is desired), and the 'Fast — no re-encoding' note adds a performance-oriented use case. However, it does not explicitly mention alternatives or exclusions, such as using extract_audio to save the audio track instead of removing it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behavior (aspect ratio preservation when one dimension is omitted, percentage scaling), but does not address edge cases such as mutual exclusivity of percent vs dimensions, what happens if neither is given, or the optionality of output_path.
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?
A single, well-structured sentence conveys the core functionality and key usage constraints. Every word earns its place with no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple resizing tool with a schema that explains all parameters, the description is largely complete. It does not elaborate on output behavior or format support, but these are inferable and not critical for this operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing a baseline of 3. The description adds value by clarifying the relationship between width/height ('missing one keeps aspect ratio') and offering a percentage alternative, which is not fully explicit in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Scale a video') and the resource ('video'), specifying the outcome ('new resolution'). It distinguishes itself from sibling tools like crop_video or compress_video by focusing on resolution scaling.
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?
There is no explicit guidance on when to use this tool over alternatives like crop_video or compress_video. The description only explains how to provide dimensions, not the situational context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It discloses that both video and audio are affected and that fades go to/from black, which is useful. However, it does not clarify what happens if no fade durations are supplied (e.g., does it error or do nothing?) or whether output_path is required to avoid overwriting the input file. These gaps prevent a higher score.
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 a single, well-structured sentence that conveys the core functionality without any redundant or tangential information. It is front-loaded and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's relative simplicity (4 parameters, no nested objects, no output schema), the description covers the primary use case but leaves some edge cases unaddressed, such as default behavior when both fade_in and fade_out are omitted and the exact role of output_path (whether it is required or defaults to overwriting). This is a moderate gap in completeness, so a score of 3 is appropriate.
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?
The input schema already provides 100% description coverage for all four parameters, so the baseline is 3. The description does not add additional parameter-level semantics beyond what the schema already states; it merely rephrases the fade_in/fade_out durations implicitly via 'start and/or end.'
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Fade' and clearly identifies the resource ('the video (and its audio)') and the exact behavior ('in from black at the start and/or out to black at the end'). This makes the tool's purpose unmistakable and distinguishes it from sibling video editing tools like trim_video or convert_video.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool is for adding fade effects, which implicitly tells an agent when to use it. However, it does not explicitly mention alternatives or exclusions, such as 'use trim_video for cutting segments instead.' The absence of explicit alternatives is not misleading, so this is a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds that the operation is 'optionally limited to a time range,' which is useful behavioral context not in the schema. However, it does not disclose output behavior (whether input is overwritten or output_path is required), which matters for an edit operation. The description also doesn't mention that mode defaults to blur, though the schema covers that.
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 a single sentence with an em dash, front-loading the core action and then giving use cases. It is concise and contains no filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 10 parameters and no annotations/output schema, this is a moderately complex tool. The description gives a clear high-level purpose and mentions the optional time range, but doesn't cover output-path handling or coordinate/time formats (though schema covers parameter details). For an edit tool, a note on output behavior would enhance completeness.
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?
The input schema has 100% parameter description coverage, so the schema already documents all 10 parameters. The description adds implicit context by referring to 'rectangle of the frame' (x/y/width/height) and 'time range' (start/end), but doesn't go beyond the schema. With complete schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Blur or pixelate a rectangle of the frame' with specific use cases (faces, license plates). This is a specific verb+resource that distinguishes it from sibling tools like crop_video or draw_box, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear use-case context: 'for hiding faces, license plates, names, or other sensitive content.' It implies when to use this tool (obscuring sensitive content) but does not explicitly mention alternatives or when not to use it. Given the sibling tools like crop_video and draw_box, explicit exclusions would strengthen it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does reveal that the GIF uses an optimized color palette and warns about file size growth, which is useful. However, it omits important behavioral details such as default output behavior when output_path is omitted, supported input formats, or overwrite semantics.
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 two sentences long, front-loaded with the main function, and includes a practical usage hint in the second sentence. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters and no output schema or annotations, the description is adequate but not fully complete. It covers the core purpose and gives a key usage constraint, but leaves gaps like default output location and format support, which are not covered by the schema or annotations.
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?
The schema already documents 100% of parameters, so the baseline is 3. The description adds some contextual meaning by implying that start/duration are used to select a section and that frame rate/width/duration should be limited to keep GIFs small, but it does not add specific syntax or format details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts a video or section into an animated GIF, using a specific verb ('Turn') and resource (video→GIF). It also mentions an optimized color palette, which distinguishes it from sibling video-processing tools that do not create GIFs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (when a GIF is needed from a video) and even offers practical guidance to keep GIFs short and small. It does not explicitly mention alternatives or exclusions, but no sibling tool creates GIFs, so the use case is effectively unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the disclosure burden. It does add useful behavior—'video is untouched'—and explains the multiplier semantics. However, it leaves out details about what happens if output_path is omitted, whether the input is overwritten, or any side effects.
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 a single, front-loaded sentence that conveys the core purpose, provides an example, and states a key nuance. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with three documented parameters and no output schema, the description covers the essential behavior and parameter semantics. It lacks explicit handling of the optional output_path (e.g., overwrite behavior), but the core functionality is well explained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 adds real meaning to the 'factor' parameter with concrete examples ('2 = double volume, 0.5 = half'), going beyond the schema's generic 'Volume multiplier (e.g. 1.5, 0.5)'. This justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Make the audio louder or quieter.' It also notes 'video is untouched,' which distinguishes it from sibling tools that manipulate video. This is clear and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the multiplier usage ('2 = double volume, 0.5 = half'), providing clear context. However, it does not explicitly state when to use this tool over alternatives like remove_audio or replace_audio, nor does it mention exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses that the tool returns a list of cut times and is a detection operation (non-destructive), but does not elaborate on edge cases (e.g., no cuts found) or output format specifics. This is adequate but not rich.
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 two sentences, front-loaded with the core action, followed by the output's use case. Every word earns its place, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 must explain return values, which it does ('Returns a list of cut times'). It also connects to sibling tools for a complete workflow. Minor gaps include lack of timestamp format details or handling of edge cases, but overall it is complete for a simple detection tool.
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% and both parameters have descriptive text in the schema (e.g., threshold sensitivity range and default, input_path purpose). The description itself does not add parameter-level detail beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Find') and identifies the resource ('timestamps where the picture changes abruptly'), clearly distinguishing it from siblings like detect_silence and editing tools. It also explains the output's purpose (cut times for trimming/concat), making the tool's function unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states that the returned cut times can be fed into trim_video/concat_videos, giving clear downstream usage context. It does not explicitly mention when not to use it or alternatives, but the intended workflow is clear enough for an AI agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds a key trait: 'Fast — no re-encoding,' which highlights performance and output quality. However, it omits other behavioral details such as how conflicting parameters (plays vs. target_duration) are resolved, whether existing output files are overwritten, or any format compatibility constraints. This is sufficient for a simple tools but leaves some gaps.
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 exceptionally concise: two sentences that front-load the core purpose and then add a valuable performance trait. Every word earns its place, with no redundancy or filler. It is well-structured for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with four parameters and no output schema, the description covers the essential behavioral aspects: the two looping modes and the 'no re-encoding' characteristic. It is mostly complete, though it does not specify behavior when neither 'plays' nor 'target_duration' is provided, or what the default output path is. These are minor gaps given the schema fills in parameter details.
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?
The input schema already has 100% description coverage for all four parameters, so the baseline is 3. The description reinforces the two modes ('a number of times' vs 'fill a target duration') but does not add detailed semantics beyond what the schema provides. It correctly aligns with the schema's parameter descriptions, giving no additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Repeat a video back-to-back a number of times, or long enough to fill a target duration.' It specifies the action (repeat), the resource (video), and the two modes (count-based or duration-based). This distinguishes it from all sibling tools, which perform other video operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context by explaining the two modes of operation: repeating a specific number of times or filling a target duration. While it doesn't explicitly state when not to use this tool or name alternatives, none of the sibling tools serve the same looping purpose, so the guidance is adequate. It implies that this is the go-to tool for video looping.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It adds the useful detail that audio pitch is preserved and explains factor semantics, but it does not disclose what happens when output_path is omitted (e.g., whether it overwrites the source or writes to a default location), nor does it describe return behavior. This is a notable gap for a write operation.
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 exceptionally concise: two sentences, clear verb-first structure, and every word earns its place. The examples are embedded efficiently without any fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations and an output schema, the description adequately covers the core functionality and parameter semantics, but it leaves a significant gap: the behavior when output_path is not provided. It also does not mention any side effects or processing limitations. This makes it a minimum-viable description, not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes all three parameters with 100% coverage, giving a baseline of 3. The description goes beyond the schema by providing concrete examples for 'factor' (2 = twice as fast, 0.5 = half speed) and adding the audio-pitch-preservation context, which enhances parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Speed up or slow down a video' identifies a specific verb and resource, and the examples (factor 2, 0.5) clarify exactly what it does. This distinguishes it from siblings like resize_video or adjust_volume.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool: whenever a video's playback speed needs changing. It provides concrete factor examples, giving clear context. However, it does not explicitly mention alternatives or exclusions, so it stops short of a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey the safety and read-only nature. It opens with 'Read metadata,' which implies a non-destructive operation, but it does not explicitly state that the file is not modified, nor does it mention potential errors, permissions, or file type limitations. The listed return fields add some transparency about output, but it is not comprehensive.
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 two sentences: the first enumerates the exact metadata fields returned, and the second provides a clear usage directive. Every word contributes value, and the structure is front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the function is a simple metadata read with one parameter and no output schema, the description is complete. It lists all key return values and places the tool in the broader workflow ('Use this first...'). The rich sibling context (16 editing tools) makes its role as a pre-edit inspection tool obvious, and nothing important is missing.
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 for the single parameter 'input_path' is 100%, with a clear description in the schema. The description adds the context that the path can point to video or audio files and that metadata will be read, but it does not add format, path-format, or validation details beyond the schema. This meets the baseline for 100% coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Read') and resource ('metadata from a video or audio file'), and lists concrete output fields (duration, resolution, frame rate, codecs, bitrate, file size). This clearly distinguishes it from all sibling tools, which are editing or transformation operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states 'Use this first to understand a file before editing it,' which provides a clear usage context. However, it does not explicitly mention when not to use it or name alternative tools for other scenarios, though sibling names are all editing tools, making the intent clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral transparency. It does not disclose whether the tool creates a new file, what the default output behavior is, or that re-encoding vs stream copy affects accuracy. It does add context about time formats, but that is more parameter semantics than behavioral disclosure.
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 just two sentences, front-loaded with the core purpose and containing zero filler. Every sentence adds useful information about usage and time formats.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main usage pattern for trimming, but it omits that the start parameter is optional (defaults to beginning of file per schema), and it does not mention the default output_path behavior. With six parameters and no output schema, these gaps make it slightly incomplete for a broader understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides full descriptions for all six parameters (100% coverage), so the baseline is 3. The description adds meaningful value by explaining that times can be seconds (12.5) or clock form (1:23:45.6) and by clarifying the rule for omitting both end and duration. This goes beyond the schema's individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Cut' with the resource 'video' and clearly defines the scope as 'a time range', distinguishing it from siblings like crop_video (spatial cropping) and concat_videos (joining videos). It is immediately clear what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit instructions on how to specify parameters: provide a start time plus either an end time or duration, and that omitting both keeps everything from start to file end. It also explains accepted time formats. However, it does not mention when to use this tool over alternatives, such as when to prefer fast_copy for quick cuts versus re-encoding for precision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It usefully reveals that bitrate is computed from duration and that omitting target size triggers quality-based compression. However, it does not mention potential side effects like overwriting existing files, default output behavior, or codec choices, leaving some behavioral aspects undisclosed.
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 two concise sentences, front-loaded with the primary action ('Shrink a video's file size'). Every sentence earns its place without redundancy or irrelevant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the tool's core functionality and both usage modes despite the lack of annotations and output schema. It omits some operational details (e.g., default output path, error conditions), but for a straightforward compression tool, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage for parameters is 100%, so the baseline is 3. The description adds meaningful context for target_size_mb by explaining the bitrate-duration relationship and the optionality behavior, which goes beyond the schema's simple description. This adds real value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Shrink a video's file size' with a specific verb and resource, clearly distinguishing it from sibling tools like resize_video or trim_video. This is unambiguous and immediately communicates the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on how to use the tool, describing two modes (target size in MB or quality-based compression) and explaining the bitrate computation. It does not explicitly mention when to use this tool versus specific siblings, so it lacks direct exclusions or alternatives, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses key behaviors: clips are normalized to the first clip's resolution/frame rate, and crossfade or hard cuts are applied. It does not mention audio handling or whether inputs are modified, but the most relevant behaviors are covered.
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 two sentences long, front-loaded with the core action, and includes a useful detail about normalization without any fluff. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, no output schema, and no annotations, the description is reasonably complete. It explains the concatenation behavior and normalization, which are the most important aspects. It doesn't mention potential side effects like overwriting output, but the schema's output_path description covers where the result goes.
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?
The input schema covers 100% of parameters with clear descriptions. The description adds only the normalization context, which is not directly tied to a specific parameter. Baseline of 3 is appropriate since the schema already documents parameter meanings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool concatenates two or more videos into one file in the order given, with hard cuts or crossfade. It uses a specific verb and resource, and the normalization detail distinguishes it from video stacking or editing tools like stack_videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (joining videos sequentially) and mentions the order of inputs, but it does not explicitly contrast with alternatives like stack_videos or picture_in_picture. Clear context is provided, but no explicit exclusions or alternative tool names are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the burden of disclosing behavior. It clearly indicates this is a read-only analysis (find, returns) and describes the output structure (silent ranges and keep-segments). It does not explicitly state 'does not modify the input' but that is strongly implied by the verb 'Find' and the return semantics, making it transparent enough.
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 two sentences, front-loaded with the main purpose, and includes a practical usage tip. Every word earns its place, with no fluff or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality, output, and intended usage, which is sufficient for a tool with 3 parameters and no output schema. It lacks some explicit details like the format of ranges (e.g., start/end times) but these are inferable from the schema and the tool's nature. Overall, it is complete for an agent to select and invoke correctly.
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?
The input schema has 100% coverage with descriptions for all three parameters (noise_db, input_path, min_duration). The description does not add additional parameter semantics beyond the schema, which is the baseline for full coverage. No extra clarification needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Find silent stretches in the audio track.' It also specifies the output ('Returns silent ranges plus the non-silent segments to keep') and distinguishes it from sibling tools by mentioning downstream use with trim/concat tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear use case: 'useful for cutting dead air' and even suggests feeding keep-segments into trim_video/concat_videos. It does not explicitly mention when not to use or name alternatives, but the context is sufficiently clear for an agent to decide when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals a key behavioral trait: 'Buffers the whole clip in memory', and also notes that audio is reversed alongside video. This goes beyond the basic purpose and helps the agent anticipate resource use and suitability. It does not mention other side effects (e.g., metadata loss), but the disclosed behaviors are the most critical.
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 two sentences with no filler. The first sentence states the primary purpose, and the second provides a critical caveat with actionable advice. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema), the description covers the essential context: purpose, audio behavior, memory constraint, and usage recommendation. It is complete enough for an agent to decide when to use it and what to expect, though it could optionally note output behavior or lack of metadata preservation for absolute completeness.
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?
The input schema already describes both parameters (input_path and output_path) with 100% coverage. The description does not add additional parameter-specific semantics beyond the schema, so the baseline score of 3 applies. It does mention trimming first, which indirectly relates to input length, but that's more of a usage guideline than a parameter clarification.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Play the video (and audio) backwards') with a clear resource (the video) and explicitly notes it affects audio as well. This distinguishes it from sibling tools like change_speed or trim_video, which address different transformations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'best for short clips — trim first for anything over a minute or two' implies when to use and recommends a preceding action (trimming). It does not explicitly name alternative tools or state 'when not to use' beyond the length caveat, but the guidance is actionable and specific.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the responsibility. It discloses key behavior: evenly-spaced sampling, timestamps on tiles, and a single output image. It lacks mention of overwrite semantics or format constraints, but for a media-generation tool, the disclosed behavior is sufficient to set expectations.
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 two sentences, 28 words, front-loading the action and output. Every word contributes; there is no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool of moderate complexity, the description explains the purpose, the output, and the workflow. A minor gap is the optional output_path not having a default mentioned, and no explicit mention of image format. These are minor and do not undermine task completion.
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?
The schema covers all five parameters with descriptions and constraints (count, columns, tile_width, input_path, output_path), so the description is not required to compensate. The description adds no parameter-specific guidance beyond the schema, matching the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies a clear verb and resource: 'Tile evenly-spaced frames from across the video into one image'. It also adds distinctive details (timestamp stamping) that separate it from sibling tools like extract_frame or detect_scenes, making the tool's purpose highly unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit context for when to use the tool: 'Use this to SEE what's in a video before deciding how to edit it'. This tells the agent the intended workflow. However, it does not name alternatives or state when not to use it, so it stops short of full exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behaviors: clips are normalized to the first clip's size, and audio comes from the first clip that has any. This goes beyond the schema and helps set expectations for output characteristics.
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?
Two sentences, front-loaded with the main purpose, followed by precise behavioral details. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential behavior for a stacking tool, including layout options, size normalization, and audio selection. Given the small parameter set and full schema coverage, it is sufficiently complete, though it could mention output format or edge cases.
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 description coverage is 100%, so the baseline is 3. The description adds slight context about input ordering (first clip as reference) but does not significantly enhance understanding of the parameters beyond the schema's own descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool arranges videos in horizontal, vertical, or grid layouts, using the verb 'stack' implicitly through 'Play videos side by side...'. It differentiates from siblings like concat_videos (sequential) and picture_in_picture (overlay) by focusing on multi-video layouts for comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly indicates 'great for comparisons', which provides a clear use case. It does not mention when-not-to-use or alternatives, but the context is sufficient for an agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behaviors: images are shown in order, shown for a fixed number of seconds, optionally with a soundtrack, and 'Images are fitted to the first image's size.' This adds important context beyond the schema, though it could be more precise about how fitting works (crop vs stretch).
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 two sentences, front-loaded with the core purpose, and includes only essential behavioral details. Every sentence earns its place with no redundancy or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and lack of output schema, the description covers the essential purpose, input behavior, and a key constraint (fitting to first image size). It is complete enough for an agent to invoke correctly, though it could mention the output format (though that is in the schema) or edge-case behaviors.
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?
The schema provides 100% coverage for parameter descriptions, so the baseline is 3. The tool description does not add additional parameter-level meaning beyond what the schema already states; for example, audio_path is already described as 'Optional soundtrack (trimmed to the slideshow length)' in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Build a video from a list of images' with specific details about ordering, fixed duration, and optional soundtrack. This distinguishes it from siblings like create_gif or concat_videos, as it is specifically for creating a video from images.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (creating a slideshow from images) and implies the use case. It does not explicitly name alternatives or exclusions, but given the sibling tools, there is no direct alternative for this function, so the guidance is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides critical behavioral details: overlay audio is dropped, main video audio is kept, and overlay disappears when its clip ends. This goes beyond typical expectations and helps the agent understand side effects.
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 two sentences, front-loaded with the core purpose, and every sentence adds value (behavioral details). No redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description covers purpose, key behaviors, and edge cases (overlay ending). It could mention what happens if the overlay is longer than the main video or default dimensions, but schema covers defaults. Overall, it's complete enough for a moderately complex tool.
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 covers all parameters with descriptions (100% coverage), so the description adds minimal extra meaning. The baseline of 3 applies because the schema already does the heavy lifting for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool overlays one video on another in a corner, with relatable examples (webcam feed, reaction box). This distinguishes it from sibling tools like add_watermark (image overlay) or stack_videos (side-by-side).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool via the scenario examples, but does not explicitly contrast with alternatives. It's clear enough for an agent to infer use cases, but lacks explicit 'use instead of' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It reveals a non-obvious trait: 'The output ends when the shorter of the two ends, unless loop_audio is set.' This gives the agent important predictive insight into output duration. However, it does not mention other side effects like whether the input file is modified or whether there are format constraints.
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 two sentences, front-loaded with the primary function, and includes a specific behavioral detail. Every word earns its place; there is no redundant or vague phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 4-parameter tool with no output schema and no nested objects, the description covers the essential purpose, parameter interaction, and a key behavioral rule. It is adequate for an agent to invoke correctly, though it could potentially mention output behavior or compatibility but this is not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 adds value by explaining the interaction between video length, audio length, and loop_audio: 'output ends when the shorter of the two ends, unless loop_audio is set.' This goes beyond the individual parameter descriptions and helps the agent understand how parameters combine.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Replace a video's audio track with a different audio file' followed by concrete examples ('background music or a voiceover'). This distinguishes it from sibling tools like extract_audio, remove_audio, and adjust_volume, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context for when to use the tool ('e.g. background music or a voiceover') and explains the default behavior with loop_audio, implying when that parameter should be set. It does not explicitly name alternative tools for different audio operations, but the purpose is clear enough for an agent to infer appropriate usage.
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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