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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose focused on specific meeting bot operations. There is no overlap between actions like creating bots, deleting data, getting status/transcripts/recordings, controlling bot speech/chat, or sending media. The descriptions make each tool's unique function immediately apparent.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case throughout. The naming convention is perfectly uniform, using clear action verbs like create, delete, get, make, remove, and send paired with specific nouns describing the operation's target.
Tool Count5/5
With 11 tools, the server provides comprehensive coverage for meeting bot management without being overwhelming. This count is well-scoped for the domain, offering a complete set of operations for bot lifecycle, data retrieval, and interaction capabilities.
Completeness5/5
The toolset offers complete CRUD/lifecycle coverage for meeting bots: creation, status monitoring, data retrieval (transcripts, recordings, chats), interaction (speaking, messaging, media sharing), and removal/deletion. There are no obvious gaps, and agents can perform all essential meeting bot workflows seamlessly.
Average 2.9/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No high-severity vulnerability alerts
- No code scanning findings
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{
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  ]
}
```
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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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get' implies a read operation, but doesn't cover aspects like authentication needs, rate limits, error conditions, or what happens if the bot_id is invalid. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource. However, it could be slightly more structured by including key details, but it earns high marks for brevity.
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?
Given the complexity (a read operation with no annotations and no output schema), the description is incomplete. It doesn't explain the return format (e.g., text, JSON), potential errors, or how it integrates with sibling tools. For a tool that likely returns data, more context is needed to guide the agent effectively.
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%, with the single parameter 'bot_id' clearly documented in the schema. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain where to find the bot_id or its format). Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Get') and resource ('transcript from a meeting bot'), making the basic purpose clear. However, it's vague about what 'transcript' entails (e.g., full text, formatted, with timestamps) and doesn't distinguish it from siblings like 'get_chat_messages' or 'get_recording', which might overlap in function. This meets the minimum viable threshold but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't specify if this is for post-meeting retrieval only, or how it differs from 'get_chat_messages' (which might handle real-time chat). The description offers no context on prerequisites or exclusions, leaving the agent to infer usage.
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, the description carries full burden but provides minimal behavioral context. It states the bot will 'join a meeting and record/transcribe it', implying mutation (creation) and data capture, but lacks details on permissions, rate limits, what happens if the bot fails, or whether recording is automatic. This is inadequate for a tool with potential 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action. It avoids redundancy and wastes no words, though it could be slightly more structured (e.g., separating creation from functionality).
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?
Given the complexity (creating a bot with recording/transcribing capabilities), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., bot ID, status), error conditions, or behavioral nuances, leaving significant gaps for an agent to use it effectively.
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 both parameters ('meeting_url' and 'bot_name') with descriptions. The description adds no additional meaning beyond implying the meeting_url must be for Zoom, Google Meet, or Teams (hinted in schema), resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('create a bot') and its purpose ('to join a meeting and record/transcribe it'), specifying the resource (bot) and its function. It distinguishes from siblings like 'remove_meeting_bot' or 'get_meeting_transcript' by focusing on creation, but doesn't explicitly differentiate from other creation-related tools (none listed).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., meeting access), exclusions, or compare to siblings like 'send_chat_message' for interaction. The description implies usage for recording/transcribing meetings but offers no contextual boundaries.
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 full burden for behavioral disclosure. It states the destructive action ('Delete') but lacks critical details: whether deletion is permanent, requires specific permissions, has rate limits, or what happens on success/failure. For a destructive tool with zero annotation coverage, this is a significant gap in transparency.
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, efficient sentence that front-loads the core action ('Delete all data') and includes helpful examples ('recordings, transcripts, etc.'). There is zero wasted verbiage, making it highly concise and well-structured.
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?
Given this is a destructive tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like irreversibility, permissions, or response format, leaving the agent under-informed for a high-stakes operation. The description should compensate more for the lack of structured data.
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%, with the single parameter 'bot_id' fully documented in the schema. The description adds no additional parameter semantics beyond implying the bot_id identifies the target for deletion. This meets the baseline of 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and target ('all data associated with a bot'), including examples of what data is deleted ('recordings, transcripts, etc.'). It distinguishes from siblings like 'remove_meeting_bot' (which likely removes the bot itself) by focusing on data deletion. However, it doesn't explicitly contrast with siblings, preventing a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., bot existence), exclusions (e.g., irreversible action), or comparisons to siblings like 'remove_meeting_bot'. This leaves the agent without context for tool selection.
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 states it 'Get[s] the current status' but doesn't specify what 'status' entails (e.g., online/offline, active/inactive, error states), whether it's a read-only operation, any rate limits, or authentication needs. This leaves significant gaps for a tool with no annotation coverage.
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, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.
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?
Given no annotations and no output schema, the description is incomplete for a tool that retrieves status information. It doesn't explain what 'status' means, potential return values, or behavioral traits like safety or performance. For a read operation with undefined output, this lacks necessary context.
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%, with the parameter 'bot_id' clearly documented in the schema as 'ID of the bot to check'. The description adds no additional meaning beyond this, such as format examples or context about bot IDs. Baseline 3 is appropriate since the schema does the heavy lifting.
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 verb 'Get' and the resource 'current status of a meeting bot', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_chat_messages' or 'get_meeting_transcript' that also retrieve information about bots/meetings, so it misses full sibling distinction.
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?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_chat_messages' and 'get_meeting_transcript' that might retrieve related data, there's no indication of context, prerequisites, or exclusions for choosing this specific status-checking tool.
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 but only states the basic action. It doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires specific permissions, how messages are returned (e.g., format, pagination), or any rate limits, leaving significant gaps in understanding.
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, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core purpose without unnecessary elaboration.
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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., message list format, timestamps), behavioral constraints, or how it integrates with sibling tools, making it inadequate for a tool that likely involves data retrieval.
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 description coverage is 100%, with the single parameter 'bot_id' well-documented in the schema. The description adds no additional meaning beyond implying the bot is associated with the meeting, so it meets the baseline for high schema coverage without extra value.
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 verb 'Get' and the resource 'chat messages from the meeting', making the purpose understandable. It doesn't explicitly differentiate from siblings like 'get_meeting_transcript' or 'send_chat_message', but the core action is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't specify if this retrieves all messages, recent ones, or how it differs from 'get_meeting_transcript' or other chat-related tools, leaving the agent without context for selection.
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 the tool retrieves a URL but doesn't explain what the URL provides (e.g., audio/video format, accessibility), whether it requires specific permissions, or any rate limits. This leaves significant gaps for a tool that likely involves media access.
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, clear sentence with zero waste, front-loading the key action and resource. It's appropriately sized for a simple tool, making it easy to scan and understand quickly.
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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like authentication needs or what the returned URL entails, which are crucial for a media retrieval tool. This leaves the agent with insufficient context to use the tool effectively.
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% description coverage, fully documenting the 'bot_id' parameter. The description adds no additional meaning beyond the schema, such as format examples or constraints, so it meets the baseline for high schema coverage without enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('recording URL for a bot'), making the purpose understandable. It doesn't explicitly differentiate from siblings like 'get_bot_status' or 'get_meeting_transcript', which might also retrieve bot-related information, so it lacks sibling distinction for a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a bot with a recording available) or compare to siblings like 'get_meeting_transcript' for related data, leaving usage context implied at best.
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 full burden but lacks behavioral details. It doesn't disclose permissions needed, rate limits, whether speech interrupts other audio, or what happens if the bot isn't in a meeting. 'Make a bot speak' implies a mutation, but no further context is given.
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, efficient sentence that directly states the tool's function without redundancy. It's front-loaded with the core purpose and uses minimal words to convey the essential action, making it highly concise and well-structured.
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?
Given the tool's complexity (mutating bot behavior in meetings) and lack of annotations or output schema, the description is incomplete. It doesn't cover error conditions, response format, or integration with meeting context, leaving significant gaps for an AI agent to understand full usage.
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 well-documented in the schema. The description adds no additional meaning beyond implying text-to-speech conversion, which is already clear from the tool name and schema. Baseline 3 is appropriate as the schema handles parameter semantics adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('make a bot speak') and the mechanism ('using text-to-speech'), specifying both verb and resource. It distinguishes from siblings like send_chat_message or send_image_to_meeting by focusing on speech output, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., bot must be in a meeting), exclusions, or comparisons to siblings like send_chat_message for text-based communication, leaving usage context implied.
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 full burden for behavioral disclosure. It states the action ('Remove') but doesn't clarify if this is destructive, reversible, requires specific permissions, affects meeting functionality, or has side effects. For a mutation tool with zero annotation coverage, this is inadequate.
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, efficient sentence with zero wasted words. It's front-loaded with the core action and target, making it immediately understandable without unnecessary elaboration.
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 mutation tool with no annotations and no output schema, the description is incomplete. It lacks behavioral context (e.g., permanence, permissions), doesn't explain what happens after removal, and offers no guidance on usage relative to siblings. Given the complexity of modifying meeting state, this leaves significant gaps.
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 description coverage is 100%, with the single parameter 'bot_id' fully documented in the schema. The description doesn't add any parameter details beyond what the schema provides, such as format examples or contextual meaning. Baseline 3 is appropriate when the schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Remove') and target ('a bot from a meeting'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'delete_bot_data' or explain how removal differs from deletion, which prevents a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives like 'delete_bot_data' or 'create_meeting_bot'. It doesn't mention prerequisites (e.g., bot must be in a meeting), exclusions, or contextual triggers, leaving the agent to infer usage from the name alone.
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 mentions sending a message but does not cover critical aspects like required permissions, potential side effects (e.g., if it triggers notifications), rate limits, or response format. This leaves significant gaps 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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.
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?
Given that this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits, usage context, and what to expect upon invocation, which is insufficient for effective agent use despite the concise structure.
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% description coverage, with clear documentation for both parameters ('bot_id' and 'message'). The description does not add any additional meaning beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send a chat message') and the resource ('from the bot to the meeting'), making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'make_bot_speak' or 'send_image_to_meeting', which might have overlapping contexts, so it lacks full sibling distinction.
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?
The description provides no guidance on when to use this tool versus alternatives such as 'make_bot_speak' or 'send_image_to_meeting', nor does it mention prerequisites like needing an active meeting or bot. It only states what the tool does without context for selection.
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 full burden for behavioral disclosure. While it indicates this is a sending/display operation, it doesn't describe what happens to the image (is it displayed temporarily/permanently?), whether it requires specific bot permissions, what happens if the meeting isn't active, or any rate limits. For a tool that presumably interacts with live meetings, this leaves significant behavioral questions unanswered.
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 extremely concise - a single sentence that communicates the core functionality and key constraint. Every word earns its place with no redundant information or unnecessary elaboration. The structure is front-loaded with the main action and target.
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?
Given this is a meeting interaction tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after sending (success/failure indicators), whether the image persists, how users see it, or any error conditions. For a tool that modifies meeting state, more behavioral context is needed despite the concise description.
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 fully documents both parameters (bot_id and image_url). The description doesn't add any additional parameter context beyond what's in the schema - it doesn't explain where to get bot_id values, what image formats are supported, or any constraints on image_url beyond HTTPS. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send an image') and target ('to the meeting through the bot'), with the specific platform constraint 'Google Meet only' providing useful context. However, it doesn't explicitly differentiate from sibling tools like 'send_video_to_meeting' or 'send_chat_message', which would require mentioning it's specifically for visual media display rather than text or video.
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?
The description provides minimal guidance - it mentions 'Google Meet only' which sets a platform constraint, but offers no advice on when to use this tool versus alternatives like 'send_video_to_meeting' or 'send_chat_message', nor does it mention prerequisites (like needing a bot created first) or appropriate use cases for image sharing versus other communication methods.
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 mentions the platform constraint ('Google Meet only'), which is useful, but fails to describe critical behaviors like whether this action is reversible, what permissions are required, how the video is displayed, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant 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 a single, efficient sentence with no wasted words. It front-loads the core action and includes the platform constraint concisely, making it easy to parse quickly.
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?
Given the complexity of sending media in a meeting context, no annotations, and no output schema, the description is insufficient. It lacks details on behavioral outcomes, error conditions, or integration with sibling tools like 'create_meeting_bot'. For a tool that likely involves mutations and platform-specific constraints, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (bot_id and video_url) adequately. The description adds no additional semantic context beyond implying the video is played by the bot, which is already suggested by the parameter names. Baseline 3 is appropriate when the schema handles parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('send a video') and target ('to the meeting'), specifying the resource (video) and platform constraint ('Google Meet only'). It distinguishes from siblings like 'send_image_to_meeting' by specifying video content, though it doesn't explicitly contrast with other media-sending tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'send_image_to_meeting' or 'make_bot_speak', nor does it mention prerequisites such as needing a bot created via 'create_meeting_bot'. The description only states the basic function without context for selection.
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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