NotebookLM MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
Most tools have distinct purposes targeting specific notebook operations (e.g., audio_overview_create vs. video_overview_create, notebook_add_drive vs. notebook_add_text). However, some potential confusion exists between notebook_query (querying existing sources) and research_start (finding new sources), though descriptions clarify this distinction. The various 'create' tools for different content types (flashcards, infographic, mind_map, etc.) are well-differentiated by their output formats.
Naming Consistency5/5Tool names follow a highly consistent snake_case pattern with clear verb_noun structure throughout (e.g., notebook_create, notebook_list, source_delete, research_start). The naming convention is uniform across all 32 tools, making them predictable and easy to parse. Even complex operations like save_auth_tokens and studio_status maintain this consistent pattern.
Tool Count3/5With 32 tools, the count feels heavy for a notebook management server, though the domain is broad (notebook CRUD, source management, content generation, research). While many tools are justified (e.g., different content creation types), the number approaches the upper limit of what's manageable. A more streamlined set might combine some similar creation tools or reduce redundancy in source management operations.
Completeness5/5The tool surface provides comprehensive coverage of the notebook management domain. It includes full CRUD for notebooks and sources, multiple content generation options (audio, video, reports, quizzes, etc.), research workflows with start/status/import tools, and administrative functions like authentication and synchronization. There are no apparent gaps - agents can perform complete notebook lifecycles from creation through content generation to deletion.
Average 3.7/5 across 32 of 32 tools scored. Lowest: 2.9/5.
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 status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'Add pasted text as source,' implying a write/mutation operation, but doesn't disclose behavioral traits such as required permissions, whether the addition is permanent or reversible, rate limits, or what the output schema returns. This leaves significant gaps for an agent to understand the tool's behavior 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by a structured 'Args:' section. There's no wasted text, and each part serves a clear function. It could be slightly more concise by integrating the args into the main description, but overall it's efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is partially complete. It covers the basic action and parameters but lacks behavioral context and usage guidelines. The presence of an output schema means return values don't need explanation, but other aspects like error handling or side effects are missing. This results in a description that meets minimum viability but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters ('notebook_id', 'text', 'title') with brief notes ('Notebook UUID', 'Text content to add', 'Optional title'), adding basic meaning beyond the schema's type definitions. However, it doesn't explain format details (e.g., UUID structure, text length limits, title default behavior), leaving parameters partially documented. With 0% coverage, this is a minimal but adequate effort.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add pasted text as source') and identifies the target resource ('source' in a notebook). It distinguishes this from sibling tools like 'notebook_add_drive' or 'notebook_add_url' by specifying text content. However, it doesn't explicitly contrast with 'source_describe' or 'source_get_content', which are read operations, leaving some ambiguity about sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 an existing notebook), exclusions (e.g., not for editing existing text), or compare it to siblings like 'notebook_create' for initial setup or 'source_delete' for removal. Usage is implied only by the action name, with no explicit context.
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 'Get notebook details with sources' which implies a read-only operation, but doesn't specify permissions needed, rate limits, error handling, or what 'sources' entails (e.g., metadata, content, or references). This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the main purpose, followed by a brief parameter note. It avoids unnecessary verbosity, though the structure could be slightly improved by integrating the parameter information more seamlessly rather than as a separate 'Args' section.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which should cover return values), the description is moderately complete for a simple retrieval tool. However, with no annotations and minimal parameter details, it lacks context on behavioral aspects like error cases or usage constraints, making it adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal parameter semantics by specifying 'notebook_id: Notebook UUID', which clarifies the format beyond the schema's basic string type. However, with 0% schema description coverage and only one parameter, this provides some value but doesn't fully compensate for the lack of schema details (e.g., validation rules or examples).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with the verb 'Get' and resource 'notebook details with sources', making it specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'notebook_describe' or 'notebook_list', which would require more precise scope definition.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'notebook_describe' or 'notebook_list' from the sibling list. It mentions retrieving details with sources but doesn't clarify if this is for a specific notebook ID only or how it differs from other notebook-related tools.
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 burden. 'Rename a notebook' implies a mutation operation, but it doesn't disclose behavioral traits like whether this requires specific permissions, if the rename is reversible, what happens to the old title, or any rate limits. For a mutation tool with zero annotation coverage, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose in the first sentence. The Args section is structured but could be more integrated. There's minimal waste, though it could be slightly more polished by combining the purpose and parameter explanations into a smoother flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and simple parameters, the description is somewhat complete but lacks crucial context for a mutation tool. It covers the basic what and parameters but misses behavioral details like permissions, side effects, and error conditions that would help the agent use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds basic semantics by explaining that notebook_id is a 'Notebook UUID' and new_title is the 'New title', which clarifies the purpose of each parameter. However, it doesn't provide format details (e.g., UUID format, title length limits) or examples, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'rename' and resource 'notebook', making the purpose immediately understandable. It distinguishes from siblings like notebook_create, notebook_delete, and notebook_describe by focusing specifically on renaming. However, it doesn't explicitly differentiate from all potential rename-like operations in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 an existing notebook), when not to use it, or how it relates to siblings like notebook_describe or notebook_get. The agent must 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 states the tool checks status and gets URLs, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, what the URLs point to (e.g., generated content files), or any error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with the core purpose stated in the first sentence. The 'Args:' section is structured but could be more integrated. There's no wasted text, but it might benefit from slightly more detail to enhance clarity without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (one parameter, no annotations, but with an output schema), the description is minimally adequate. It covers the basic purpose and parameter but lacks context on usage, behavioral traits, and integration with sibling tools. The presence of an output schema means return values are documented elsewhere, but the description doesn't reference this, leaving gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal parameter semantics: it specifies that 'notebook_id' is a 'Notebook UUID', which clarifies the format beyond the schema's generic 'string' type. However, with 0% schema description coverage and only one parameter, this is a baseline case. The description compensates slightly but doesn't fully explain what a valid UUID looks like or where to obtain it, leaving room for improvement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check studio content generation status and get URLs.' It specifies the verb ('Check') and resource ('studio content generation status'), and distinguishes it from siblings like 'research_status' by focusing on 'studio' content. However, it doesn't explicitly differentiate from all possible alternatives, such as 'notebook_get', which might also provide status information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 mentions 'notebook_id' as a required parameter but doesn't explain prerequisites, such as needing a notebook created via 'notebook_create' or 'research_start'. There's no mention of when not to use it or what alternatives exist among the many sibling tools.
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 burden. It implies a write operation ('Add') but doesn't disclose behavioral traits such as permissions needed, whether the addition is reversible, how it interacts with existing sources, or error handling. The mention of 'doc_type' with options hints at supported formats, but lacks details on validation or defaults beyond the schema's 'default: doc'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a structured 'Args:' section that efficiently documents parameters. Every sentence earns its place with no redundant information, 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.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema description coverage, but an output schema exists, the description is minimally adequate. It covers the basic purpose and parameters, but as a write operation tool, it lacks details on behavioral context, error cases, and integration with sibling tools. The output schema likely handles return values, so completeness is borderline viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'Drive document ID (from URL)', 'Display title'), adding meaning beyond the bare schema. However, it doesn't fully detail constraints like UUID format for 'notebook_id' or valid 'doc_type' values beyond the listed options, leaving gaps in parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add') and resource ('Google Drive document as source'), making the purpose immediately understandable. It distinguishes this tool from sibling tools like 'notebook_add_text' and 'notebook_add_url' by specifying it's for Drive documents. However, it doesn't explicitly contrast with 'source_sync_drive' or 'source_list_drive', which slightly limits differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'notebook_add_text', 'notebook_add_url', or other source-related tools. It mentions no prerequisites, constraints, or typical scenarios for adding Drive documents, leaving the agent to infer usage from context 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 states the action ('Add') but doesn't describe what 'Add' entails—e.g., whether it creates a new source, appends to existing content, requires permissions, or has side effects. For a mutation 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a clear Args section. Every sentence earns its place: the first defines the action, and the second documents parameters. It's appropriately sized with zero waste, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), the description doesn't need to explain outputs. However, with 2 parameters, 0% schema coverage, and no annotations, the description is minimal—it covers the basics but lacks details on behavior, error cases, or integration context. It's adequate as a starting point but has clear gaps for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists the two parameters (notebook_id and url) with brief explanations, but schema description coverage is 0%, meaning the schema provides no details. The description adds basic semantics (e.g., 'Notebook UUID', 'URL to add'), which compensates partially. However, it doesn't specify URL formats, validation rules, or notebook_id constraints, leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add URL') and resource ('as source'), specifying it accepts websites or YouTube URLs. It distinguishes from sibling tools like notebook_add_text and notebook_add_drive by focusing on URLs, though it doesn't explicitly contrast them. The purpose is specific but lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 notebook_add_text or notebook_add_drive. It mentions the resource type (URLs) but doesn't specify contexts, prerequisites, or exclusions. Usage is implied only by the tool name and brief description, with no explicit when/when-not instructions.
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 burden. While 'Configure' implies a mutation/write operation, the description doesn't disclose important behavioral traits: whether this requires specific permissions, if changes are reversible, what happens to existing settings, rate limits, or what the response contains. The parameter documentation adds some context but doesn't address core behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise: a clear purpose statement followed by well-organized parameter documentation. Every sentence earns its place, with no wasted words. The Args section uses bullet-like formatting that's easy to parse while remaining compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations but with an output schema (which handles return values), the description is moderately complete. The parameter documentation is thorough, but behavioral aspects (permissions, side effects, error conditions) are missing. For a configuration tool that presumably changes system behavior, more context about what 'configure' actually does would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate - and it does well by explaining all 4 parameters in the Args section. It clarifies notebook_id is a UUID, goal has specific values (default|learning_guide|custom), custom_prompt requirements and constraints, and response_length options. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Configure') and resource ('notebook chat settings'), making it immediately understandable. However, it doesn't distinguish this configuration tool from its many siblings (like notebook_create, notebook_describe, etc.), which would require explicit differentiation to earn a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 many sibling tools available (notebook_create, notebook_describe, notebook_query, etc.), there's no indication of when chat configuration is appropriate versus other notebook operations or what prerequisites might 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 full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose any behavioral traits such as pagination, sorting, error conditions, or rate limits. For a tool with no annotations, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose in the first sentence and parameter details in a structured 'Args' section. Every sentence earns its place without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema, the description is reasonably complete. It covers the purpose and parameter semantics adequately, though it lacks behavioral details that would be helpful despite the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'notebook_id' is a 'Notebook UUID', which clarifies the parameter's purpose beyond the schema's type definition. However, it doesn't provide format examples or constraints, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all mind maps in a notebook'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'notebook_list' or 'source_list_drive', which list different resources, 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 Guidelines2/5Does 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 implies usage for listing mind maps, but it doesn't specify prerequisites, exclusions, or compare to other list tools in the sibling set, leaving the agent without contextual 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Create a new notebook' which implies a write/mutation operation, but it doesn't mention any behavioral traits such as permissions required, whether creation is idempotent, what happens on failure, or the format of the output (though an output schema exists). 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured: a clear purpose statement followed by a brief parameter explanation. Every sentence earns its place with no wasted words, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter) and the presence of an output schema, the description is minimally adequate. However, as a mutation tool with no annotations, it lacks context on behavioral aspects like error handling or prerequisites. The output schema mitigates the need to describe return values, but overall completeness is limited.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'title' by describing it as 'Optional title for the notebook', which clarifies its purpose beyond the schema's basic type and default. With 0% schema description coverage and only one parameter, this adequately compensates, though it could specify constraints like length or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Create') and resource ('a new notebook'), making the purpose immediately understandable. However, it doesn't differentiate this tool from other creation tools like 'audio_overview_create', 'data_table_create', or 'flashcards_create' that exist among the sibling tools, which would require specifying what makes a notebook distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 multiple creation tools available (e.g., 'notebook_create', 'audio_overview_create', 'quiz_create'), there's no indication of what a 'notebook' is or when it's the appropriate choice over other content types, leaving usage context unclear.
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 the tool 'Get[s] AI-generated notebook summary,' implying it's a read-only operation that uses AI, but doesn't disclose critical traits like whether it requires authentication, has rate limits, or how it handles errors. The description adds minimal context beyond the basic action, leaving gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first in a clear sentence. The additional 'Args' and 'Returns' sections are structured but slightly redundant since the output schema exists. Every sentence adds value, but it could be more concise by omitting the return details given the output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema (which handles return values), the description is mostly complete. It covers the purpose and parameter semantics well. However, it lacks behavioral details like authentication or error handling, which are important given no annotations, preventing a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema. The schema has 0% description coverage, only defining 'notebook_id' as a required string. The description specifies that 'notebook_id' is a 'Notebook UUID,' clarifying the parameter's format and purpose. Since there's only one parameter, this compensation is effective, though it doesn't detail constraints like UUID format examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get AI-generated notebook summary with suggested topics.' It specifies the verb ('Get'), resource ('notebook'), and output types ('summary', 'suggested_topics list'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'notebook_get' or 'notebook_query', which might also retrieve notebook information, so it doesn't reach 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 Guidelines2/5Does 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 sibling tools such as 'notebook_get' (which might fetch raw notebook data) or 'notebook_query' (which could search notebooks), leaving the agent without context for tool selection. The only implied usage is based on the purpose, but no explicit when/when-not rules are given.
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 it's a list operation, implying it's read-only, but doesn't confirm this or mention other traits like rate limits, pagination behavior (beyond the max_results parameter), or what happens if no notebooks exist. The description lacks details on return format, error conditions, or performance characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured. The first sentence 'List all notebooks.' front-loads the core purpose clearly. The 'Args:' section efficiently documents the parameter without unnecessary elaboration. Every sentence earns its place, with zero wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (a simple list operation with one optional parameter) and the presence of an output schema (which handles return values), the description is minimally complete. It covers the purpose and parameter semantics adequately. However, for a tool with no annotations, it should ideally include more behavioral context (e.g., read-only nature, pagination hints) to fully guide an agent, leaving some gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'max_results' by explaining it's the maximum number of notebooks to return and providing its default value (100). Since schema description coverage is 0% (the schema only defines the type and default without a description), the description fully compensates by clarifying the parameter's purpose and default behavior, making it easy for an agent to use correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'all notebooks', making the purpose immediately understandable. It distinguishes from siblings like notebook_create, notebook_describe, and notebook_query by focusing on listing all notebooks without filtering or querying. However, it doesn't explicitly differentiate from mind_map_list, which is a similar listing operation for a different resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 when to choose notebook_list over notebook_query (which likely allows filtering) or notebook_get (which retrieves a specific notebook). There's no context about prerequisites, such as whether authentication is needed or if it works with all notebook types.
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 the tool is 'AI-generated' and returns a summary with keywords, but lacks details on permissions, rate limits, processing time, or error handling. For a tool with no annotation coverage, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first. The 'Args' and 'Returns' sections are structured clearly, though the use of markdown formatting in the description might be slightly verbose. Overall, it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema (implied by 'Returns'), the description is fairly complete. It explains the parameter semantics and return format adequately. However, the lack of behavioral details and usage guidelines prevents a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context beyond the input schema. The schema only specifies 'source_id' as a string with 0% description coverage, but the description clarifies it's a 'Source UUID' and explains the return values ('summary (markdown with **bold** keywords), keywords list'), which compensates well for the low schema coverage. Since there's only one parameter, the baseline is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get AI-generated source summary with keyword chips.' It specifies the verb ('Get'), resource ('source summary'), and key features ('AI-generated', 'keyword chips'). However, it doesn't explicitly differentiate from sibling tools like 'source_get_content' or 'notebook_describe', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 sibling tools like 'source_get_content' (which might retrieve raw content) or 'notebook_describe' (which might describe notebooks), leaving the agent to infer usage context. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that the tool requires user confirmation ('confirm=True after user approval'), which is a crucial behavioral constraint. However, it doesn't mention whether this is a read-only or destructive operation, what permissions are needed, or what happens to existing mind maps. The description adds some behavioral context but leaves significant gaps 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.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise with two sentences, but the structure is inefficient. The first sentence states the purpose and constraint, while the second sentence lists parameters with brief explanations. However, the parameter explanations are terse and could be better integrated. The description avoids redundancy but doesn't optimally front-load the most critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (which handles return values), no annotations, and 4 parameters with 0% schema coverage, the description is moderately complete. It covers the purpose, a key behavioral constraint (confirmation), and lists parameters. However, for a creation tool that likely produces persistent artifacts, it should better explain what 'Generate' entails, what resources are consumed, and provide more parameter context to compensate for the schema coverage gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all 4 parameters but provides minimal semantic context: 'notebook_id: Notebook UUID' and 'source_ids: Source IDs (default: all)' add some meaning, while 'title: Display title' and 'confirm: Must be True after user approval' are somewhat helpful. However, critical details are missing: what format UUIDs should be, what 'Source IDs' refer to, what happens when source_ids is null, or what 'user approval' entails.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate and save mind map') and resource ('mind map'), making the purpose evident. It distinguishes from sibling 'mind_map_list' by focusing on creation rather than listing. However, it doesn't specify what exactly is being generated from (e.g., notebook content), leaving some ambiguity compared to other creation tools like 'infographic_create'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the tool: 'after user approval' with 'confirm=True'. This establishes a clear prerequisite condition for invocation. However, it doesn't mention when NOT to use it or explicitly differentiate from similar creation tools like 'infographic_create' or 'quiz_create' that might also work with notebooks.
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 mentions the prerequisite condition (research_status must be 'completed'), it doesn't describe what 'import' actually does operationally - whether it copies, moves, or transforms data; what permissions are required; whether it's idempotent; what happens if sources are already imported; or what the output looks like. For a mutation tool with zero annotation coverage, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence serves a purpose - the first states what the tool does, the second provides crucial timing context, and the Args section documents parameters. However, the parameter documentation could be more integrated with the main description rather than in a separate Args section.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given 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, 3 parameters (2 required), 0% schema description coverage, but WITH an output schema, the description is moderately complete. The timing prerequisite is valuable, and parameter explanations help, but for a tool that presumably modifies notebook state by importing research sources, more behavioral context about what 'import' entails would be beneficial despite the existence of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description partially compensates by explaining all three parameters in the Args section: notebook_id as 'Notebook UUID', task_id as 'Research task ID', and source_indices as 'Source indices to import (default: all)'. This adds meaningful context beyond the bare schema, but doesn't provide format details (like what constitutes valid indices) or explain the relationship between task_id and the research process mentioned in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Import discovered sources') and target ('into notebook'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'notebook_add_drive' or 'notebook_add_url' which also add content to notebooks, leaving some ambiguity about how this tool differs from those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit timing guidance ('Call after research_status shows status="completed"'), which is excellent context for when to use this tool. However, it doesn't mention when NOT to use it or provide alternatives for similar operations, nor does it explain the relationship with the 'research_start' sibling tool that presumably initiates the research process.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds value by specifying the confirm requirement for user approval, which hints at a mutation operation needing consent. However, it lacks details on side effects (e.g., what gets created, rate limits, or response format), leaving gaps for a tool with 7 parameters and output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose and confirm requirement in the first sentence. The Args section is structured but includes some redundancy (e.g., repeating 'default: all' and enum values already in schema). Overall, it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters with 0% schema coverage, an output schema exists (so return values needn't be explained), and no annotations, the description is moderately complete. It covers all parameters briefly and includes the confirm requirement, but lacks behavioral context like what the video overview entails or error conditions, making it adequate but with clear gaps for a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all 7 parameters with brief explanations (e.g., 'Notebook UUID', 'Source IDs (default: all)'), adding meaning beyond the bare schema. However, explanations are minimal (e.g., 'BCP-47 code' without examples beyond en/es/fr/de/ja), and it doesn't clarify interactions like how source_ids=null differs from an empty array, leaving significant gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Generate video overview' with specific parameters like notebook_id and format, making the verb+resource combination explicit. However, it doesn't distinguish this tool from sibling tools like 'slide_deck_create' or 'infographic_create' beyond the 'video' aspect, missing sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context with 'Requires confirm=True after user approval', indicating when to use this tool (after approval) and implying a prerequisite. It doesn't explicitly state when not to use it or name alternatives among siblings, but the approval requirement offers practical guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that CSRF and session ID are 'auto-extracted' from request components, which is useful behavioral context about how the tool processes inputs. However, it doesn't disclose important traits like whether this operation requires specific permissions, what happens to existing tokens, whether it's idempotent, or what authentication state changes occur. The description adds some value but 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by an 'Args:' section detailing each parameter. Each sentence serves a purpose: the first states the tool's function and auto-extraction behavior, while parameter descriptions explain sources and deprecation status. Some minor verbosity exists in repeating 'auto-extracted' concepts, but overall it's efficiently organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's authentication-focused purpose, 5 parameters with 0% schema coverage, no annotations, but with an output schema present, the description provides reasonably complete context. It explains what the tool does, how parameters relate to each other (deprecation relationships), and data sources. The output schema existence means return values don't need description. However, for an authentication tool with potential security implications, more behavioral context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 5 parameters, the description provides crucial semantic information. It explains that 'cookies' should come from 'Cookie header from Chrome DevTools get_network_request', clarifies that csrf_token and session_id are deprecated and auto-extracted, and specifies that request_body and request_url are optional sources for token extraction. This adds substantial meaning beyond the bare schema, though it could provide more detail about expected formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Save NotebookLM cookies' with the verb 'save' and resource 'cookies'. It distinguishes itself from sibling tools by focusing on authentication token management rather than content creation or notebook operations. However, it doesn't explicitly contrast with any specific authentication-related siblings since none appear in the list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through references to 'Chrome DevTools get_network_request' and auto-extraction from request components, suggesting this tool is used when capturing network traffic for authentication. However, it doesn't provide explicit guidance on when to use this tool versus alternatives (like manual token management or other auth methods) or any prerequisites for successful operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses the confirmation requirement (important behavioral constraint) and implies this is a generation/mutation operation. However, it doesn't describe what 'audio overview' actually produces, potential side effects, permissions needed, rate limits, or error conditions - 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.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized but not optimally structured. The first sentence states purpose and key constraint, which is good front-loading. However, the Args section uses inconsistent formatting (some parameters have explanations in parentheses, others don't) and could be more efficiently integrated with the main description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters with 0% schema coverage, no annotations, but with an output schema present, the description does a reasonably complete job. It explains all parameters and their semantics, states the confirmation requirement, and the output schema means return values don't need explanation. The main gap is lack of behavioral context about what the tool actually produces and any constraints beyond confirmation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 7 parameters, the description compensates well by explaining all parameters in the Args section. It provides meaning for each parameter beyond just names: notebook_id is a 'Notebook UUID', source_ids default to 'all', format has specific enum values, etc. The only gap is that 'confirm' parameter semantics ('Must be True after user approval') could be more explicit about workflow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate audio overview' with a specific verb ('Generate') and resource ('audio overview'). It distinguishes from siblings like 'video_overview_create' by specifying audio format, but doesn't explicitly differentiate from other content generation tools like 'report_create' or 'slide_deck_create'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool: 'Requires confirm=True after user approval' establishes a prerequisite workflow. It doesn't explicitly state when NOT to use it or name specific alternatives among siblings, but the confirmation requirement provides practical guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the confirmation requirement ('Requires confirm=True after user approval'), which is valuable behavioral context. However, it doesn't disclose other important traits like whether this is a read/write operation, what permissions are needed, whether it's destructive, rate limits, or what the output looks like beyond generating an infographic.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized but not optimally structured. The first sentence states the purpose, but the parameter explanations are presented in a separate 'Args:' section rather than integrated into a cohesive narrative. While all information is useful, the two-part structure could be more fluidly integrated for better front-loading of key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, confirmation requirement) and the presence of an output schema (which means return values don't need explanation), the description provides good contextual completeness. It covers the confirmation workflow, explains all parameters meaningfully, and states the core purpose. The main gap is lack of behavioral context about permissions, side effects, or error conditions that annotations would normally provide.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 7 parameters, the description provides substantial value by explaining each parameter's purpose and constraints. It clarifies that 'notebook_id' is a UUID, 'source_ids' defaults to all sources, 'orientation' has three specific options, 'detail_level' has three levels, 'language' uses BCP-47 codes with examples, 'focus_prompt' is optional text, and 'confirm' must be True after approval. This compensates well for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with the verb 'Generate' and resource 'infographic', making it immediately understandable. It distinguishes itself from siblings like 'slide_deck_create' or 'report_create' by specifying it creates visual infographics rather than other content types. However, it doesn't explicitly differentiate from all siblings (e.g., 'mind_map_create' also creates visual content).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool: 'after user approval' with 'confirm=True'. This gives important guidance about the confirmation requirement before execution. However, it doesn't specify when NOT to use this tool or mention alternatives among the many sibling tools for different content types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses the confirm requirement for user approval, which is a key behavioral trait. However, it doesn't mention other important behaviors like whether this is a read/write operation, potential side effects, rate limits, or what happens when source_ids is null. The description adds some value but 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.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably structured with a purpose statement followed by parameter explanations. However, it could be more front-loaded - the key requirement about user approval is buried. Some sentences like 'Generate report' are overly terse, while the parameter explanations are clear but could be more efficiently integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters with 0% schema coverage and no annotations, the description does a good job explaining parameter semantics and the confirm requirement. The presence of an output schema means the description doesn't need to explain return values. For a report generation tool with multiple parameters, this provides adequate context though more behavioral transparency would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for 6 parameters. It provides meaningful context for all parameters: notebook_id as UUID, source_ids default behavior, report_format options, custom_prompt requirement, language as BCP-47 codes, and confirm's purpose. This adds substantial value beyond the bare schema, though it doesn't explain parameter interactions in depth.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Generate report' with specific parameters like notebook_id and report_format. It distinguishes from siblings by focusing on report generation rather than other content types like flashcards, quizzes, or mind maps. However, it doesn't explicitly differentiate from similar tools like 'slide_deck_create' or 'infographic_create' which might also generate content from notebooks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Requires confirm=True after user approval' and specifies when custom_prompt is required. It implicitly suggests this is for report generation from notebooks, but doesn't explicitly state when to use this vs. alternatives like 'slide_deck_create' or 'quiz_create' for different output formats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the confirmation requirement workflow and default parameter behaviors, but doesn't describe mutation effects, permission needs, rate limits, or what the generated quiz contains. It adequately covers the confirmation constraint but lacks broader behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sections: a summary sentence and a parameter explanation block. Every sentence adds value, though the structure could be more front-loaded by integrating parameter defaults into the main description rather than separating them.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, mutation operation) and absence of annotations, the description provides good coverage of parameters and workflow. The existence of an output schema means return values don't need explanation. It adequately covers the core functionality but could better address mutation implications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining all 5 parameters in the Args section. It clarifies notebook_id as a UUID, source_ids defaults to all sources, question_count and difficulty have defaults, and confirm requires True after approval. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Generate quiz') and identifies the resource (quiz). It distinguishes from siblings like 'flashcards_create' or 'report_create' by specifying quiz generation, but doesn't explicitly contrast with other content creation tools beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use the tool ('Requires confirm=True after user approval'), establishing a prerequisite workflow. However, it doesn't specify when NOT to use it or name alternatives among sibling tools, leaving some ambiguity about tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses the critical behavioral trait: requires user approval via confirm=True. However, it doesn't mention other important behaviors like whether this is a destructive operation, what permissions are needed, rate limits, or what happens to existing slide decks. The description adds some value but 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured: purpose statement first, then parameter details in a clear format. Every sentence earns its place by providing essential information. Minor improvement possible by integrating the confirm requirement more seamlessly with the purpose statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters with 0% schema coverage and no annotations, the description does a good job explaining parameter semantics. The presence of an output schema means return values don't need explanation. For a content generation tool with user approval requirement, the description covers the essential context, though could better address behavioral aspects like what 'generate' entails operationally.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides meaningful semantics for all 7 parameters: explains notebook_id is a UUID, source_ids default behavior, format options, length options, language codes, focus_prompt purpose, and confirm requirement. This adds substantial value beyond the bare schema, though some details like BCP-47 code examples could be more complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate slide deck' specifies the verb and resource. It distinguishes from siblings like 'infographic_create' or 'report_create' by focusing on slide decks specifically. However, it doesn't explicitly differentiate from other content generation tools beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Requires confirm=True after user approval' indicates when to use it (after approval) and implies a prerequisite interaction. It doesn't explicitly mention when NOT to use it or name specific alternatives among siblings, but the approval requirement provides practical guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the confirm requirement (a safety/validation behavior) and implies this is a creation/mutation operation. However, it doesn't describe what happens during generation, whether it's idempotent, what permissions are needed, or what the output contains. The behavioral disclosure is minimal but includes a critical safety constraint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with a clear two-part structure: purpose statement followed by parameter explanations. Every sentence earns its place, though the formatting with 'Args:' could be more integrated. It's front-loaded with the core purpose and key requirement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters with 0% schema coverage and no annotations, the description does a good job explaining parameter meanings and the confirm requirement. The existence of an output schema means return values don't need explanation. For a creation tool with safety constraints, it covers the essentials though could benefit from more behavioral context about what generation entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides meaningful semantics for all 4 parameters: notebook_id as 'Notebook UUID', source_ids as 'Source IDs (default: all)', difficulty with values 'easy|medium|hard', and confirm as 'Must be True after user approval'. This adds substantial value beyond the bare schema, though it doesn't explain parameter interactions or constraints in depth.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and resource 'flashcards', making the purpose specific and understandable. It distinguishes from siblings like quiz_create or mind_map_create by focusing on flashcards specifically. However, it doesn't explicitly differentiate from other content generation tools in terms of output format or use case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Requires confirm=True after user approval.' This clearly indicates when to use the tool (after user approval) and establishes a prerequisite condition. It doesn't mention alternatives, but the confirm requirement is a strong contextual guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the critical behavioral trait of requiring user approval via the confirm parameter, which is essential for a creation tool. However, it doesn't mention other important behaviors like whether this operation is reversible, what permissions are needed, rate limits, or what happens on failure. The description adds some value but leaves significant behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear opening sentence followed by a well-organized Args section. Every sentence earns its place: the first establishes the core action and critical constraint, while the Args provide essential parameter context. No wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a creation tool with 5 parameters, 0% schema coverage, and no annotations, the description does a reasonably complete job. The presence of an output schema means the description doesn't need to explain return values. The description covers the approval requirement and parameter meanings adequately, though it could better address behavioral aspects like error conditions or side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for the schema's lack of parameter documentation. The Args section provides meaningful explanations for all 5 parameters, clarifying what each represents (e.g., 'Notebook UUID', 'Description of the data table to create', 'Source IDs (default: all)'). It adds substantial value beyond the bare schema, though it could provide more detail about format expectations for source_ids or language codes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and resource 'data table', making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'notebook_add_text' or 'report_create', which also create content within notebooks. The description could better explain what makes a 'data table' distinct from other content types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance with 'Requires confirm=True after user approval' and repeats this in the Args section. This clearly indicates when to use the tool (after user approval) and includes a prerequisite condition. While it doesn't mention specific alternatives among siblings, the approval requirement serves as a strong contextual guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a blocking operation that waits for completion or timeout, includes polling behavior with configurable intervals, and mentions token-saving truncation with the 'compact' parameter. However, it doesn't cover error handling, rate limits, or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose and blocking behavior. The parameter explanations are structured in a bullet-like format under 'Args:', making it easy to scan. Every sentence adds value without redundancy, and there's no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (blocking with polling) and the presence of an output schema (which handles return values), the description is largely complete. It covers purpose, behavior, and parameter semantics well. However, it lacks details on error cases (e.g., what happens if the notebook_id is invalid) and doesn't mention sibling tools for context, which could help in tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate fully. It adds significant meaning beyond the schema by explaining all four parameters: 'notebook_id' as a Notebook UUID, 'poll_interval' as seconds between polls with a default, 'max_wait' as max seconds to wait with details on the 0 value, and 'compact' as a boolean for truncating reports to save tokens. This provides clear semantics that the schema alone lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Poll research progress' with the specific action of blocking until completion or timeout. It distinguishes itself from siblings like 'research_start' (initiates research) and 'studio_status' (checks studio status) by focusing on polling progress. However, it doesn't explicitly differentiate from 'notebook_query' or 'notebook_describe' which might also provide status information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning 'Blocks until complete or timeout,' suggesting it should be used when waiting for research completion. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'notebook_query' or 'notebook_describe' for status checks, nor does it mention prerequisites (e.g., needing a started research).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the tool's behavior as listing sources with freshness status, which implies a read-only operation. However, it doesn't disclose other behavioral traits like whether it requires authentication, rate limits, pagination, or error conditions. The description adds some context about freshness status but lacks comprehensive behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured. It uses two sentences: the first states the purpose, and the second provides usage guidance. The parameter explanation is brief and directly relevant. There is no wasted text, and key information is front-loaded effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (listing with freshness status), no annotations, and an output schema present, the description is reasonably complete. It covers purpose, usage, and parameter semantics. The output schema likely handles return values, so the description doesn't need to explain them. However, it could benefit from more behavioral details like authentication needs or error handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds parameter semantics beyond the input schema. The schema has 0% description coverage and only defines notebook_id as a required string. The description explains that notebook_id is a 'Notebook UUID,' clarifying its format and purpose. With only one parameter and no schema descriptions, this additional context is valuable and compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List sources with types and Drive freshness status.' This specifies the verb ('List'), resource ('sources'), and key attributes ('types and Drive freshness status'). It distinguishes from siblings like source_describe or source_get_content by focusing on listing with freshness status. However, it doesn't explicitly differentiate from source_sync_drive beyond usage guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Use before source_sync_drive to identify stale sources.' This clearly states when to use this tool (before source_sync_drive) and why (to identify stale sources), directly naming an alternative tool. It effectively guides the agent on tool selection in context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool performs a sync operation (implying mutation) and requires user confirmation, which is useful behavioral context. However, it lacks details on potential side effects, error handling, or performance characteristics like rate limits, leaving gaps 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by prerequisites and parameter explanations in a structured format. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and 2 parameters with 0% schema coverage, the description does a good job covering purpose, usage, and parameter semantics. It's complete enough for basic use, though it could benefit from more behavioral details like error cases or sync scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics: 'source_ids: Source UUIDs to sync' clarifies the parameter's purpose and format, and 'confirm: Must be True after user approval' explains the requirement and rationale. This compensates well for the lack of schema descriptions, though it doesn't cover all possible nuances.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Sync') and resource ('Drive sources with latest content'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'source_list_drive' beyond mentioning it as a prerequisite, so it doesn't fully achieve sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: 'Call source_list_drive first to identify stale sources.' It also specifies a prerequisite condition: 'Requires confirm=True' and 'Must be True after user approval,' clearly indicating the context and approval needed before invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the core behavior (querying existing notebook sources with AI) but lacks details on permissions, rate limits, response format, or error conditions. It adds some context about default behavior for source_ids but is otherwise minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement, usage guidelines, and parameter explanations in bullet points. Every sentence adds value without redundancy, and it's front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations, but with an output schema), the description covers purpose, usage, and parameters adequately. The output schema likely handles return values, so the description doesn't need to explain those. It could benefit from more behavioral details but is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides meaningful semantics for all 4 parameters: notebook_id (Notebook UUID), query (Question to ask), source_ids (Source IDs to query with default behavior), and conversation_id (For follow-up questions). This compensates well for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Ask AI about EXISTING sources already in notebook') and distinguishes it from sibling tools by explicitly contrasting with 'research_start' for finding new sources. It precisely defines the scope and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Ask AI about EXISTING sources already in notebook') and when not to use it ('NOT for finding new sources'), with a named alternative ('Use research_start instead for: deep research, web search, find new sources, Drive search'). This clearly differentiates it from sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses key behavioral traits: it's a read operation ('Get'), returns raw text without AI processing, and is performance-optimized ('Much faster'). However, it doesn't mention error conditions, rate limits, authentication needs, or what happens with invalid source IDs, leaving some behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Perfectly structured and front-loaded: first sentence states purpose, second explains scope, third gives performance comparison. The Args/Returns section is cleanly separated. Every sentence earns its place with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with 0% schema coverage and an output schema (implied by Returns section), the description does well: it explains the parameter, lists return values, and provides usage context. However, it doesn't mention authentication requirements or error handling, which could be important for a tool accessing potentially sensitive content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides the parameter name ('source_id') and clarifies it's a 'Source UUID', adding semantic meaning beyond the bare schema. However, it doesn't explain where to find source IDs or provide format examples, leaving some practical usage gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get raw text content') and resource ('of a source'), specifying it returns original indexed text from specific formats (PDFs, web pages, etc.) and distinguishes it from sibling 'notebook_query' by noting it's faster for content export. This provides specific differentiation from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('Much faster than notebook_query for content export') and when not to use it ('no AI processing'), providing clear alternatives and context. This gives the agent precise guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates the destructive nature ('IRREVERSIBLE') and the confirmation requirement, which are critical for safe use. However, it lacks details on permissions, rate limits, or error handling, leaving some behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action and warning, followed by concise parameter explanations. Every sentence adds value: the first states purpose and risk, the second outlines usage rules, and the args section clarifies parameters without redundancy. It is efficiently structured with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive operation, 2 parameters) and no annotations, the description does well by covering purpose, irreversible risk, and confirmation requirement. With an output schema present, return values need not be explained. However, it could mention prerequisites like authentication or error scenarios for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics: 'notebook_id' is explained as a 'Notebook UUID', and 'confirm' is clarified with 'Must be True after user approval', providing context beyond the bare schema. This covers both parameters adequately, though it could detail format constraints for the UUID.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete'), resource ('notebook'), and critical characteristic ('permanently'), which distinguishes it from sibling tools like notebook_rename or notebook_describe. It specifies the irreversible nature upfront, making the purpose explicit and distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: it states 'Requires confirm=True' and 'Must be True after user approval', indicating when to use this tool (only after user confirmation) and implying when not to use it (without approval). This is clear and directive for safe invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates critical behavioral traits: the operation is irreversible (destructive), requires user confirmation (confirm=True), and permanently deletes the resource. This goes beyond what the input schema alone would indicate, providing essential safety and usage context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the most critical information first ('Delete source permanently. IRREVERSIBLE.'). The Args section is well-structured but slightly redundant with the main description. Every sentence earns its place, though the formatting could be slightly more integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no annotations, the description does an excellent job covering the essential context: purpose, irreversible nature, confirmation requirement, and parameter meanings. The presence of an output schema means return values don't need explanation. However, it could briefly mention potential side effects or dependencies, though not strictly necessary given the tool's straightforward nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage, the description fully compensates by explaining both parameters. It clarifies that source_id is a 'Source UUID to delete' and that confirm 'Must be True after user approval', adding crucial semantic meaning about the purpose and constraints of each parameter that the schema alone doesn't provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Delete source permanently') and resource ('source'), distinguishing it from sibling tools like source_describe or source_list_drive. It uses strong, unambiguous language that leaves no doubt about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (to delete a source permanently) and includes a prerequisite (requires confirm=True after user approval). However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the sibling tools, such as notebook_delete or studio_delete, which might handle different resource types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure and excels at this. It explicitly warns 'IRREVERSIBLE' (critical destructive behavior), specifies the confirmation requirement 'Requires confirm=True' (safety mechanism), and mentions the artifact source 'from studio_status' (prerequisite context). This provides comprehensive behavioral information beyond what the bare schema offers.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise: a clear purpose statement upfront, followed by a well-organized parameter explanation. Every sentence earns its place - the warning, confirmation requirement, and parameter explanations are all essential information with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given 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, 0% schema coverage, but with an output schema present, the description provides excellent coverage of the critical aspects: purpose, behavioral warnings, and parameter semantics. The main gap is that it doesn't mention what the tool returns (though the output schema handles this), and it could more explicitly differentiate from similar deletion tools in the sibling list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining all three parameters: notebook_id as 'Notebook UUID', artifact_id as 'Artifact UUID (from studio_status)', and confirm as 'Must be True after user approval'. This adds crucial semantic meaning that the schema's type definitions alone don't provide, including the relationship between parameters and prerequisite information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Delete') and resource ('studio artifact'), distinguishing it from sibling tools like notebook_delete or source_delete by specifying the artifact type. It provides a complete verb+resource combination that leaves no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (deleting studio artifacts) and includes the prerequisite 'Requires confirm=True' which indicates a safety mechanism. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the sibling tools, though the context suggests it's for studio artifacts specifically.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the asynchronous nature (research_start -> poll research_status), time estimates (fast: ~30s, deep: ~5min), result volume estimates (~10 vs ~40 sources), and constraints (deep mode is web only). It doesn't mention error conditions or rate limits, but provides substantial operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with clear sections (purpose, usage, workflow, args) and every sentence earns its place. It's front-loaded with the core purpose, followed by practical guidance, then detailed parameter explanations - all without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, asynchronous workflow, different modes/sources) and the presence of an output schema (which means return values don't need description), the description provides complete context. It covers purpose, usage workflow, parameter semantics, and behavioral expectations - everything needed for an agent to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 5 parameters, the description fully compensates by providing clear semantic explanations for all parameters: query purpose with examples, source options (web|drive), mode differences with timing/volume details, notebook_id behavior (creates new if not provided), and title purpose. This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('search web or Google Drive to FIND NEW sources') and distinguishes it from siblings by mentioning the research workflow (research_start -> poll research_status -> research_import). It explicitly identifies the resource (sources) and differentiates from other tools like notebook_create or source_list_drive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance with 'Use this for:' examples ('deep research on X', 'find sources about Y', etc.) and a clear workflow sequence. It distinguishes when to use this tool versus alternatives by specifying the research workflow and mentioning source options (web/drive).
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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