DreamingAI MCP Server

Server Quality Checklist

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Latest release: v1.0.6
Disambiguation5/5
Each tool targets a distinct resource and action, with clear separation between prompts, conversations, agents, models, and plugins. No two tools appear to perform the same operation, and even similar verbs like 'list' and 'get' are differentiated by whether they return all items or a single item.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case, with verbs like get, list, create, update, delete, send, switch, install, activate, deactivate, and uninstall. The pattern is uniform across all five domains, making the API predictable and easy to navigate.
Tool Count4/5
With 23 tools, the server is slightly above the typical 3-15 tool range, but this is justified by the breadth of functionality covering prompts, conversations, agents, models, and plugins. Each tool corresponds to a meaningful operation, and the count feels appropriate for the comprehensive scope.
Completeness5/5
The tool surface provides complete CRUD and lifecycle coverage for prompts, agents, and plugins, plus conversation management including history and messaging, and model listing/selection. There are no obvious dead ends; all core workflows for managing an AI platform are represented.
Average 3.4/5 across 23 of 23 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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

Behavior1/5
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, but it only states the action without revealing any side effects, validation, permissions, or return behavior. For a create operation, this 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 concise sentence, front-loaded with the verb and resource, containing no redundant words. It is appropriately sized for the minimal content it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters, no output schema, and no annotations, yet the description offers no context about use cases, behavior, or expected outcomes. It is far from complete 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage of all parameters with descriptions, so the baseline is 3. The tool description adds no additional meaning beyond what the schema already offers, but it does not need to compensate for missing schema information.
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 ('Create') and the resource ('a new prompt template'), distinguishing it from sibling tools like get_prompt, update_prompt, and delete_prompt. It effectively identifies the tool's core purpose.
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 create_conversation or update_prompt. The description does not mention any context, prerequisites, or exclusions, leaving the agent without situational direction.
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 responsibility for behavioral disclosure. It does not mention read-only behavior, pagination behavior (despite page params existing in schema), result scope, or any side effects. The statement 'List all' hints at a complete listing but does not elaborate on potential limits or nuances.
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 sentence that is concise, front-loaded, and free of fluff. It communicates the essential action and resource without 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?
The description is minimal for a simple list tool. It does not mention return format, pagination behavior, or how this tool fits into the broader workflow. Even though the schema covers parameters, the lack of annotations and output schema, combined with zero usage context, leaves the description incomplete for an agent to confidently select and invoke the 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 description coverage is 100% (both page and pageSize are described). The tool description adds no extra parameter context, but the baseline of 3 applies given the high 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 identifies the tool as a list operation on chat conversations/sessions in DreamingAI. While it distinguishes from create/delete/history siblings by verb and resource, it does not explicitly compare to alternatives or clarify scope (e.g., all users vs. current user).
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 siblings like get_conversation_history or create_conversation. The description is purely declarative and lacks context about prerequisites, filtering, or use cases.
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 must carry the burden of behavioral disclosure. It states 'Switch' which implies a state change, but it does not explain consequences such as whether existing conversations are affected, whether the change is persistent, or any required permissions. This is a minimal disclosure, similar to the update_drive example.
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, focused sentence with no filler or redundancy. It communicates the core action and target resource efficiently. The structure is appropriately short for the tool's simplicity.
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 absence of annotations and output schema, the description is too sparse to be contextually complete. It does not explain the optional conversationId behavior, the default vs. per-conversation distinction, or potential side effects. An agent relying solely on this description may not invoke the tool correctly without examining the schema.
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% (both modelId and conversationId have descriptions), so the baseline is 3. The tool description adds no additional parameter semantics—it does not elaborate on modelId or conversationId beyond what the schema already provides. Therefore, no extra credit beyond baseline.
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 ('Switch') and the resource ('active AI model for conversations'), which distinguishes it from siblings like list_models or get_model. However, it lacks explicit scope clarification (e.g., per-conversation vs. default), which the schema must provide. It is clear but not as strong as a description that names alternatives or exclusions.
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 does not mention that setting conversationId changes a specific conversation while omitting it changes the default, nor does it indicate any prerequisites or side effects. The description leaves usage context to the schema, which is insufficient.
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 the full burden of behavioral disclosure. It only says 'Get the message history,' implying a read operation but offering no details about pagination, ordering, default page size, or what is returned (e.g., metadata vs. full messages). It does not mention that the history is paginated or that pageSize has a default of 50, which are non-obvious behaviors. This is a significant gap for an agent invoking the tool.
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, front-loaded sentence with no fluff. It efficiently states the tool's purpose. However, it lacks additional useful guidance (such as alternatives or scope restrictions) that would make it earn a 5, but it is appropriately concise for a simple read operation.
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 has no annotations or output schema. The description does not explain the return format, message ordering, pagination behavior, or any constraints (e.g., maximum pageSize). Given that the agent must invoke this correctly, the absence of such information makes the description incomplete. Sibling tools provide some context, but the description itself lacks sufficient operational detail.
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 each parameter (conversationId, page, pageSize) having a clear description. The tool description adds no extra meaning beyond what the schema provides—it does not, for instance, explain how page and pageSize interact or that pageSize has a maximum. Therefore, 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 uses a specific verb ('Get') and resource ('message history for a specific conversation'), clearly identifying the tool's function. This distinguishes it from siblings like list_conversations (which lists conversations) and send_message (which sends messages). The addition of 'in DreamingAI' provides context but is unnecessary; the core purpose is unambiguous.
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 does not mention that list_conversations should be used to find conversation IDs, nor does it indicate any prerequisites (e.g., conversation must exist). The description simply states what the tool does, leaving the agent to infer usage from the schema and sibling names.
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?
There are no annotations provided, so the description carries the full burden for behavioral disclosure. It only states the high-level action without revealing whether the operation persists data, requires authentication, returns any identifier, or has side effects. This is a significant transparency gap for a creation 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 concise sentence that front-loads the primary action and resource. There is no redundant information or filler.
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 absence of annotations and output schema, the description is too sparse. It does not explain what the tool returns, how the created conversation is referenced afterward, or whether the optional parameters have any coupling (e.g., agentId/modelId compatibility). This incompleteness may hinder an agent from using the tool 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 three properties (title, agentId, modelId), yielding 100% schema coverage. The tool description adds no additional meaning about these parameters, so the baseline score of 3 is appropriate; 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 action ('Create') and the target resource ('a new chat conversation/session in DreamingAI'). It distinguishes this tool from sibling tools like list_conversations, delete_conversation, and get_conversation_history, which use different verbs and resources.
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 or why it should be preferred over alternatives. Sibling tools imply usage (e.g., create before send_message), but there is no explicit statement of context, prerequisites, or 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, the description carries the full burden of behavioral disclosure. It only states 'Uninstall a plugin' without explaining consequences such as whether uninstallation is reversible, whether it removes configuration/data, or whether it requires special permissions.
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 directly states the action with no unnecessary words. It is perfectly concise for a tool with one parameter.
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 the simple tool, the description omits any information about what happens after uninstall (e.g., return values, plugin state), and lacks context about when this should be used relative to deactivation. It falls short for a destructive operation.
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 pluginId with 100% coverage, so the description need not add much. The phrase 'a plugin' adds no extra meaning beyond the schema's 'ID of the plugin to uninstall', 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 the specific verb 'Uninstall' with the resource 'plugin' from DreamingAI, clearly distinguishing it from sibling tools like install_plugin and activate_plugin. It is concise 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 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 such as deactivate_plugin or install_plugin. There are no mentions of prerequisites, ordering, or 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, the description must disclose behavioral traits on its own. It only states 'Delete an AI agent' without mentioning irreversibility, potential cascading deletion of associated data, or whether the operation requires confirmation. This is a significant gap for a destructive 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 a single, concise sentence that directly states the action. It is front-loaded with the verb and object, and every word contributes to the meaning. This is an example of efficient structure.
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 simple delete operation, the description is minimal but omits critical context such as permanence, consequences, and return values. Although the schema covers the parameter, the lack of annotations and output schema means the description should provide more behavioral context than it does.
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 fully describes the single parameter agentId as 'ID of the agent to delete', and the tool description adds no extra semantic information about the parameter. Since schema coverage is 100%, the baseline score of 3 applies, and the description does not elevate it.
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: deleting an AI agent. It uses a specific verb 'Delete' and a specific resource 'AI agent', which distinguishes it from sibling tools like get_agent, create_agent, or update_agent. The addition of 'from DreamingAI' provides product context.
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 relative to alternatives. It does not mention any prerequisites, exclusions, or scenarios where this is the appropriate choice. No direction is given regarding checking for existing agents or considering destructive effects.
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 the full burden for behavioral disclosure. It only states the basic delete action, failing to mention whether deletion is permanent, whether it cascades to associated messages, or any side effects. The description adds minimal context beyond the tool name.
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, concise sentence that immediately conveys the tool's purpose. It is front-loaded and contains no extraneous words, earning a perfect score for conciseness.
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 simple delete tool with one well-documented parameter, the description is minimally adequate. However, it lacks important context for a destructive operation—such as irreversibility or side effects—and there is no output schema, making the description not fully complete for an agent's needs.
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 fully describes the single parameter (conversationId) with a clear description, achieving 100% coverage. The tool description does not add any further meaning to the parameter, 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 a specific action ('Delete') on a specific resource ('chat conversation/session') within DreamingAI. It distinguishes from sibling delete tools like delete_agent and delete_prompt by explicitly targeting conversations.
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 does not mention conditions, consequences, or exclusions, leaving the agent to infer that this is the only tool for deleting conversations.
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 adds no context beyond the action already implied by the name—no mention of irreversibility, side effects, required permissions, or impact on dependent data. For a destructive operation, this 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, clear sentence with no wasted words. It is concise and to the point, earning top marks for structure.
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 (one parameter) and the description covers the basic purpose, but it lacks usage guidance and behavioral transparency. For a destructive operation with no annotations, the description is minimally adequate but has clear gaps, making it below what would be considered complete.
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% and the only parameter 'promptId' is already well-described in the schema. The tool description adds no additional meaning beyond what the schema provides, so the baseline score of 3 applies.
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 'Delete a prompt template from DreamingAI' uses a specific verb and resource, clearly distinguishing it from sibling delete tools like delete_conversation and delete_agent. It unambiguously states 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not state when to use this tool vs alternatives, when not to use it, or any prerequisites. The intended use is only implied by the name and description.
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 bears full responsibility. It only states the high-level action without disclosing potential side effects (e.g., overwriting existing versions), required permissions, or what happens after installation.
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, focused sentence that efficiently conveys the core purpose without 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 simple one-parameter tool, the description is functional but omits useful context such as success/failure output or interplay with activation. Given the absence of annotations and output schema, a bit more detail would make it more complete.
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 fully describes the only parameter pluginId, so the description adds minimal new meaning. It provides no additional semantics beyond the schema's own description.
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 (Install), the resource (a plugin), and the source (DreamingAI marketplace), distinguishing it from sibling tools like activate_plugin and uninstall_plugin.
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 explicit guidance on when to use this tool versus siblings. The description does not mention prerequisites, the relationship to activate_plugin, or when installation should be preferred over activation/deactivation.
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 states that the tool lists plugins, but does not disclose whether the operation is read-only, what the response format is, whether pagination exists, or any other behavioral traits beyond the basic action.
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 concise sentence, front-loaded with the action 'List'. Every word earns its place with no redundancy or unnecessary detail.
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 with three optional parameters and no output schema. The description provides a clear purpose but lacks context such as the shape of the returned data, whether default filtering applies, or any limitations. This is adequate but leaves gaps for an agent invoking the 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%, so the input schema already documents all three parameters (status, keyword, category) with descriptions. The description does not add any parameter-specific meaning, but the baseline of 3 is appropriate given the 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 uses the specific verb 'List' and identifies the resource as 'plugins' in the 'DreamingAI marketplace'. It clearly distinguishes this tool from sibling mutation tools such as install_plugin, activate_plugin, etc., which perform different actions.
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. The description simply states what it does without mentioning prerequisites, use cases, or exclusions (e.g., when to use install_plugin instead).
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 must disclose behavioral traits directly, but it only states the action ('deactivate') and target ('active plugin'). It does not mention reversibility, side effects, permission requirements, or what happens to the plugin's configuration/data, which 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, concise sentence that is front-loaded with the action and resource. 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.
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 (one parameter, no output schema), the description is mostly sufficient. It implies the prerequisite that the plugin must be active, but it omits any postcondition or error behavior. Still, it covers the essential context for a basic deactivation action.
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 fully describes the single parameter 'pluginId' with a clear description and 100% coverage. The tool description adds no additional parameter-level semantics, so 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 uses a specific verb 'Deactivate' with the resource 'plugin' and qualifies it as 'active', clearly distinguishing it from sibling tools like activate_plugin and uninstall_plugin. This is a clear and unambiguous statement of purpose.
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 uninstall_plugin or activate_plugin. There is no mention of prerequisites, scenarios, or exclusions, leaving the agent without contextual decision support.
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 bares full responsibility for behavioral disclosure. It fails to mention that the tool is paginated (as evidenced by page and pageSize parameters) and that keyword filters results. The phrase 'all available' is misleading given pagination. No info on response structure or authentication is provided.
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 with zero fluff. It conveys the essential purpose immediately and is appropriately sized.
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 description omits critical operational details like pagination behavior, keyword filtering semantics, and return values. Given the absence of an output schema and annotations, this minimal description is insufficient for an agent to fully understand the tool's behavior.
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 parameters (page, keyword, pageSize) are already documented. The tool description adds no extra meaning beyond what the schema provides, earning the baseline score of 3.
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 verb ('List') and resource ('available AI agents'), clearly distinguishing it from sibling tools like get_agent or list_conversations. The scope is also explicit with 'in DreamingAI', making the purpose 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 implies usage for listing all agents, but does not explicitly mention alternatives such as get_agent for a single agent, nor does it explain when filtering via keyword would be appropriate. Context is clear but there are no exclusions or explicit alternative 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?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only says 'List all prompt templates' and does not mention pagination, filtering behavior, ordering, return format, or potential side effects. The word 'all' is potentially misleading given the page/pageSize parameters in the schema.
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 with no filler words. It efficiently communicates the core action and resource, making it easy for an agent 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 lack of annotations and output schema, the description is too thin to fully contextualize the tool. It does not clarify whether 'all' means all results or paginated pages, what fields each prompt template includes, or whether this returns a simple list or a paginated object. This is a notable gap for an agent that needs to interpret the result 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?
All 5 parameters are fully described in the input schema (100% coverage), so the description does not need to add parameter details. The description makes no reference to parameters, but the schema already provides comprehensive semantics, meeting the baseline of 3.
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 'List' and names the resource 'all prompt templates in DreamingAI', clearly distinguishing this tool from siblings like get_prompt (which retrieves a single prompt) and create_prompt/update_prompt/delete_prompt (which mutate prompts). It leaves no ambiguity about the tool's core function.
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 this tool is for listing all prompt templates, but it does not explicitly state when to use it versus alternatives, nor does it mention exclusions or filtering as an alternative. Usage context is present but not elaborated; no sibling alternatives are referenced.
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 must fully disclose behavioral traits. It only mentions sending a message and getting a response, without covering side effects, required permissions, error behavior, or any mutational implications. This is insufficient for a tool that likely writes to a conversation.
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 that efficiently states the tool's purpose without unnecessary words. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema or annotations, and the description does not explain return values, cancellation behavior, or potential errors. The tool has 3 parameters and 2 required, but the description only covers the basic action. More context is needed for an agent to fully understand 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?
The input schema provides 100% descriptive coverage for all parameters, including message, modelId, and conversationId. The description adds no additional parameter context, 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 action (send a message) and the resource (a DreamingAI conversation), and also notes the expected outcome (get an AI response). This distinguishes it from sibling tools like create_conversation or get_conversation_history.
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 a clear use case for interactive messaging, but it does not explicitly state when to use it versus alternatives or mention any prerequisites or exclusions. With no guidance on selecting this tool over siblings, it relies on the agent's 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 must convey behavioral context. It only states the action without mentioning prerequisites, side effects, required permissions, or return values, leaving the agent without a clear picture of what activation entails.
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 immediately communicates the action and target. No wasted words 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?
For a simple one-parameter tool with no output schema or annotations, the description is adequate but minimal. It lacks context about what activation means or any behavioral implications, though the simplicity of the tool reduces the need for extensive detail.
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 the parameter described as 'ID of the plugin to activate'. The description adds no additional meaning beyond this, so it meets the baseline but does not enhance 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 uses a specific verb ('Activate') and resource ('an installed plugin'), clearly indicating the tool's action and distinguishing it from siblings like install_plugin and deactivate_plugin.
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 phrase 'installed plugin' implies the plugin must already be installed, but the description provides no explicit guidance on when to use this tool versus alternatives (e.g., install_plugin, deactivate_plugin).
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 for behavioral disclosure. It only says 'Get details and capabilities', which essentially restates the tool name without elaborating on read-only nature, required permissions, error behavior, or what specific capabilities are returned.
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, front-loaded sentence with no redundant information. It efficiently communicates the tool's purpose without wasting 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?
With only one parameter and no output schema, the description is minimal but adequate. However, it lacks specificity about the exact details and capabilities returned, and provides no usage context or prerequisites, which could leave an agent uncertain about whether this tool meets its needs.
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 (modelId with description 'ID of the model to retrieve'). The description adds no additional parameter meaning beyond the schema, so the baseline score of 3 applies.
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 verb 'Get' and resource 'details and capabilities of a specific AI model', which distinguishes it from sibling tools like list_models (which lists all models) and switch_model (which changes the active model).
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 this tool is for retrieving a specific model by ID, but provides no explicit guidance on when to use it versus alternatives, nor mentions situations where it should not be used. The distinction from list_models is inferable but not stated.
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 bears full responsibility for behavioral disclosure. 'Update' signals mutation but the description does not explain whether updates are partial (only provided fields) or complete replacement, nor does it mention potential side effects, permissions, or error behavior. This is a significant 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 a single, efficient sentence with no filler or redundancy. It conveys the essential purpose in minimal words, scoring high on conciseness.
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 fully documents all parameters, but the description lacks important behavioral context such as whether updates are partial, what the return value looks like, and any error conditions. For a mutation tool with no annotations and no output schema, this leaves a notable gap, though the clear purpose and complete schema prevent it from being severely deficient.
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 descriptions cover 100% of the parameters (tags, title, content, category, promptId, description), providing clear meaning for each field. The tool description adds no additional parameter semantics beyond the schema, so 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 'Update an existing prompt template in DreamingAI' clearly identifies the action (update), the resource (prompt template), and the system (DreamingAI). It distinctly differentiates itself from sibling tools like get_prompt, create_prompt, and delete_prompt, which are named for different operations.
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 phrase 'existing prompt template' implies this tool is for modifying an already-created prompt, providing subtle usage context. However, it does not explicitly mention when to use this vs. create_prompt or get_prompt, nor does it state any exclusions or prerequisites (e.g., that the prompt must exist).
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 merely restates the tool's purpose without detailing side effects, permission requirements, irreversibility, or what the response will look like after creation.
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 that is front-loaded with the action and resource. It contains no redundant or filler content, earning a perfect score.
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?
With 7 parameters, no output schema, and no annotations, the description is under-specified. It does not indicate what the tool returns, any prerequisites (like required 'name'), or what 'custom role and behavior' entails for the agent's configuration.
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 all 7 parameters having descriptions, so the baseline is 3. The description's mention of 'custom role and behavior' adds no meaningful parameter-level information beyond what the schema already provides (e.g., 'systemPrompt' definition).
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 ('Create'), the resource ('a new AI agent'), the platform ('DreamingAI'), and the key configurable aspect ('custom role and behavior'). This unambiguously distinguishes it from sibling tools like create_conversation or create_prompt.
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 creating a new agent, as opposed to updating or deleting one. However, it does not explicitly mention alternatives (e.g., update_agent for modifications) or exclusions, so it falls short of full 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?
No annotations are provided, so the description must carry the full transparency burden. It only states 'Get details' with no mention of return format, error behavior (e.g., 404 if agent not found), authentication requirements, or that the operation is read-only. While the verb 'Get' implies a read, it is too minimal to fully disclose behavior.
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, focused sentence with no redundancy or unnecessary information. It front-loads the core action and resource, making it highly scannable.
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?
With no output schema and no description of return values, the description is incomplete for a getter tool. It fails to specify what 'details' are included, the response shape, or failure scenarios. Given the simplicity of the tool, one might expect at least a mention of the returned agent object or that not found will lead to an error.
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 the single parameter agentId with a clear description, and the schema description coverage is 100%. The tool description adds no extra semantic detail about the parameter (e.g., where to find the ID or any format constraints), so it earns the baseline score of 3.
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 verb 'Get' and the resource 'details of a specific AI agent', making it distinct from siblings like list_agents (which returns all agents) and get_prompt (a different resource). This is specific 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'specific AI agent' clearly implies the need for an agentId and establishes the context for when to use this tool. However, it does not explicitly mention alternatives or exclusions (e.g., 'use list_agents to get all agents'), so it falls short of the top score.
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 must fully disclose behavior. It only says 'update configuration' without specifying whether it's a merge or full replacement, whether permissions are required, or what the response looks like. The description adds little beyond the tool name itself.
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 verb and resource. Every word earns its place; there is no redundancy or filler.
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?
This is an 8-parameter mutation tool with no annotations and no output schema. The one-sentence description provides only the basic purpose and does not elaborate on behavior, update semantics, prerequisites, or return values. The schema covers parameters but the description leaves critical context for invocation largely implicit, making it insufficient 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter having a clear description (e.g., 'Updated name', 'ID of the agent to update'). The tool description does not add any parameter-level detail beyond what the schema already provides, so it meets the baseline 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 the specific verb 'update' and identifies the resource as 'an existing AI agent's configuration', clearly distinguishing it from create/get/delete agent tools. The scope is explicit, matching the tool's name and intent.
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 phrase 'existing' implies this tool is for modifying already-created agents, not creating or retrieving them. However, it does not explicitly name alternatives like create_agent or get_agent, nor does it state when not to use it. The context is clear but lacks explicit 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 provided, the description must convey behavioral traits. 'Get details' clearly implies a read-only operation and is non-destructive, but it does not disclose response format, error behavior, permissions, or any other side effects. The minimal wording provides only the essential read-only trait.
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, concise sentence that front-loads the action and resource. No unnecessary words or vague phrasing, and it is appropriately sized for a simple read operation.
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 tool is simple with one parameter and no nested objects, and the schema fully covers the parameter. The description clearly states what the tool does, but the absence of an output schema means the agent must infer what 'details' includes. Overall, it is reasonably complete but lacks explicit return-value 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 coverage is 100% for the single parameter 'promptId', whose description is 'ID of the prompt to retrieve'. The tool description does not add any extra meaning beyond the schema, so 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 uses a specific verb ('Get') and resource ('details of a specific prompt template') and clearly indicates it operates on a single item by ID, distinguishing it from sibling tools like list_prompts, create_prompt, update_prompt, and delete_prompt.
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 implicitly indicates this tool is for retrieving one prompt's details, but it does not explicitly state when to use it over alternatives or mention exclusions. No sibling alternatives are referenced, so usage context 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 carries the transparency burden. The verb 'List' implies a read-only operation and the phrase 'all available' discloses scope. However, it does not explicitly state non-modification, pagination, or any authentication requirements, leaving some behavioral context implicit.
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 with no redundant words. Every word contributes to conveying the action and resource, achieving maximum conciseness.
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 list tool with one optional parameter and no output schema, the description adequately conveys the core purpose and scope. It omits mention of the platform filter (though the schema covers it) and does not describe the return format, but these are minor gaps given 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?
The input schema fully describes the optional 'platform' parameter with examples and 100% coverage. The description itself does not mention the filter or add any meaning beyond the schema, so the baseline score of 3 applies.
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 identifies a list operation for all AI models/platforms in DreamingAI, using the specific verb 'List' and resource 'available AI models and platforms'. It distinguishes itself from siblings like 'get_model' (single model retrieval) and 'switch_model' (changing active model) by emphasizing 'all available'.
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 (use when you need to see all models/platforms) but provides no explicit guidance on when to use this tool versus alternatives like get_model or switch_model. No exclusions or alternative recommendations are mentioned.
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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