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

Annotations indicate readOnlyHint=false and destructiveHint=false. The description adds context on how content is added (append or insert after a block) and resolution of object_id to doc_id. It does not cover idempotency or fail states, but adds value beyond annotations.

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

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

The description is concise, well-structured with clear sections (identification, usage examples) and no wasted sentences. It effectively communicates key information.

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

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

Even without an output schema, the description covers identification, content insertion, and positioning. It is complete for a tool that adds content to a document, with no missing critical information.

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

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

Schema coverage is 100%, so baseline 3. The description adds value by explaining the priority between doc_id and object_id, and the meaning of after_block_id with examples. This goes beyond the schema descriptions.

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

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

The description clearly states 'Add markdown content to an existing monday.com document.' This is a specific verb-resource pair that distinguishes it from siblings like create_doc (create new) and update_doc (modify settings).

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

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

The description provides detailed guidance on identifying the document via doc_id or object_id, with usage examples. It does not explicitly state when not to use this tool versus alternatives, but the context is clear for adding content.

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

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

Annotations already indicate read-only, non-destructive, idempotent behavior. The description reinforces this with 'READ-ONLY' and adds context about limitations (e.g., OAuth triggers not appearing) and the structure of returned data.

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

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

The description is well-structured with clear sections (actions, examples, related tools) and is comprehensive. It could be slightly more concise, but all information is relevant and earns its place.

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

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

Given the tool's two actions and relation to other tools, the description is complete. It explains return fields, limitations, and usage in conjunction with related tools. No output schema exists, so the description compensates by detailing response structure.

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

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

Schema coverage is 100% and schema property descriptions are thorough. The tool description adds value by explaining parameter usage (e.g., 'Never guess or invent a skill id') and providing examples. While already well-covered in schema, the description enhances understanding.

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

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

The description clearly states the tool's purpose: browsing the account-wide catalog of trigger types and skills for monday platform agents. It specifies the two actions (list_triggers and list_skills) and distinguishes from sibling tools like manage_agent_triggers and manage_agent_skills.

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

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

Explicit usage guidance is provided: 'Use this tool to discover what's available BEFORE wiring anything to a specific agent.' It also explains when not to use it (e.g., OAuth triggers) and gives related tools for further actions.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that mutations are rejected with an error before the request is sent, which is valuable behavioral context beyond the annotations.

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

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

Three sentences, each adding unique value: purpose, constraint, prerequisite. No unnecessary words.

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

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

For a general GraphQL query tool, the description covers purpose, constraints, and prerequisites. There is no output schema, but return values are not expected to be detailed. Missing mention of error handling beyond mutation rejection, but overall adequate.

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

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

Schema coverage is 100% with descriptions for both parameters. The tool description does not add additional meaning beyond the schema. The schema's description of 'query' mentions 'query/mutation' which slightly contradicts the tool's read-only claim, but this is minor.

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

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

The description clearly states 'Execute read-only GraphQL queries against the monday.com API', specifying the verb (execute), resource (GraphQL queries), and constraint (read-only). It distinguishes from sibling tools that perform mutations or other operations.

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

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

The description advises using get_graphql_schema and get_type_details tools first, providing clear context. It explicitly states that mutations are rejected, helping the agent know when not to use this tool. However, it does not list specific alternative tools for similar read operations.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, indicating a safe read operation. The description adds behavioral context by specifying that it fetches schema definitions and includes details about the response content, enhancing transparency beyond annotations.

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

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

The description is well-structured with a main sentence and bullet points, but slightly verbose. It is front-loaded with the core purpose, and every sentence provides value, though some redundancy could be trimmed.

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

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

Given no parameters and no output schema, the description fully explains the tool's purpose, content, and usage scenarios. It is complete and self-contained, providing all necessary context for an agent to decide when and why to invoke it.

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

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

The input schema has zero parameters, and schema coverage is 100%. The description does not need to explain parameters but adds meaning by detailing what the tool returns and its purpose. This exceeds the baseline expectations for a parameterless tool.

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

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

The description clearly states it fetches complete JSON Schema 7 definitions for all widget types in monday.com, listing specific items like required/optional fields and validation rules. This distinguishes it from sibling tools like 'create_widget' or 'get_board_schema', which have different purposes.

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

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

The description explicitly states when to use the tool—before creating widgets to understand requirements, validate settings, and plan implementations. While it doesn't mention when not to use it, the context is clear, and no direct alternative exists among siblings.

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

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

Annotations assert readOnlyHint=true, destructiveHint=false, idempotentHint=true, and the description aligns by describing a read-only calculation. The description adds behavioral context beyond annotations, such as noting that human-friendly labels are returned in 'LABEL_<column_id>' fields. No contradiction.

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

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

The description is well-structured, starting with a clear purpose, followed by examples, then a required precondition, and an important note. However, it repeats the same examples ('total number of items') twice, making it slightly redundant. It earns its sentences but could be more succinct.

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

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

Given the tool's complexity (7 parameters, aggregations, filters, grouping) and no output schema, the description provides essential usage context (precondition, column ID guidance, LABEL field). However, it does not describe the return value structure (e.g., rows of aggregated data), leaving some gap. Still, the examples and behavioral notes give adequate completeness for most use cases.

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

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

Schema description coverage is 100%, so baseline is 3. The description provides examples of aggregations but does not add significant new meaning to individual parameters beyond what the schema already offers (e.g., columnId, function enum). The precondition and important note are valuable but pertain to pre-usage steps, not parameter semantics.

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

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

The description clearly states the tool calculates insights about board data via filtering, grouping, and aggregating columns. It provides concrete examples (total items, items per status) and distinguishes itself from siblings like get_board_info or get_board_items_page by focusing on summaries rather than raw data.

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

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

Explicitly states when to use: 'Use this tool when you need to get a summary of the board's data'. Provides a precondition to first use get_board_info if columns were added or structure is unknown. This gives clear guidance on prerequisites and appropriate contexts.

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

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

Annotations mark it as idempotent and not readOnly or destructive. The description adds that createLabelsIfMissing requires permission to change board structure. However, it does not disclose other behavioral traits like potential partial updates on failure or rate limits, which would be expected 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.

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

The description is concise (two sentences) and front-loaded with the tool's purpose. The precondition is important but could be formatted more prominently (e.g., bold or separate line). Overall, it is not verbose and every sentence adds value.

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

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

Given the simple mutation tool with 100% schema coverage and no output schema, the description covers the main purpose, precondition, and a key permission note. It could mention what the tool returns (e.g., the updated item) or error behaviors, but the core context is sufficient.

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

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

The input schema covers all 4 parameters with descriptions, achieving 100% schema coverage. The description adds concrete examples for the columnValues parameter (showing JSON structure for text, status, date, phone, email), which goes beyond the schema's generic description.

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

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

The description clearly states it changes column values of an item in a monday.com board, using a specific verb ('Change') and resource ('Item Column Values'). It distinguishes from siblings like move_item_to_group or update_column by focusing on column values and mentioning a required precondition for board-relation linking tasks.

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

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

The description includes an explicit prerequisite: for board-relation linking, call link_board_items_workflow first. It does not mention alternative tools for similar tasks (e.g., create_item, update_column) or scenarios where this tool should not be used, but the precondition provides clear context.

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

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

Annotations show readOnlyHint=false, destructiveHint=false, idempotentHint=false, which are consistent with the description's focus on configuring AI (non-read, non-destructive). The description discloses prerequisites (column must exist with compatible type) and behavior per block type, adding context beyond annotations.

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

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

The description is well-structured with sections for block types, source types, column reference syntax, and related tools. It is slightly verbose but every section adds necessary information. Front-loaded with purpose and usage.

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

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

With 16 parameters and no output schema, the description covers all necessary context: prerequisites, block-specific parameter requirements, source type explanations, column reference syntax, and related tools. It is complete for a complex configuration tool.

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

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

Schema coverage is 100%, but the description adds value by listing which parameters apply to each block type, explaining source types and column reference syntax. This helps the AI agent correctly fill parameters beyond the schema's descriptions.

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

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

The description clearly states the tool's purpose: 'Add AI to a column or set up an AI column on a monday.com board'. It lists specific use cases (categorize, summarize, translate, etc.) and distinguishes from sibling tools like create_column.

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

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

The description explicitly tells when to use this tool (e.g., 'add AI to a column', 'set up automatic extraction/categorization/summarization') and provides alternative tools (create_column for creating a column first). It also details block types, source types, and column reference syntax.

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

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

The description adds behavioral context beyond annotations: it explains that the tool translates natural language into supported blocks, may return 'needs_clarification' status, and that conditions are optional and multiple conditions imply AND. It does not contradict annotations (destructiveHint=false, idempotentHint=false). With annotations providing basic intent cues, this description adds valuable behavioral details.

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

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

The description is long but well-structured with clear sections (purpose, usage guidelines, format, rules, terminology, example). It is front-loaded with the main purpose. While every part serves a purpose, it could be slightly more concise; however, the structure aids understanding.

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

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

Given the complexity of creating automations (triggers, conditions, actions) and the lack of an output schema, the description adequately covers the input requirements, expected behavior, and potential responses (needs_clarification). It does not cover success return values, but the provided information is sufficient for an agent to select and invoke the tool correctly.

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

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

Schema coverage is 100%, so baseline is 3. The description adds significant meaning by providing a structured template for the 'userPrompt' parameter, including examples and rules for formatting. The 'boardId' parameter is simply described as 'numeric board ID as a string' in the schema, but the description confirms its usage context.

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

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

The description clearly defines the tool's purpose: creating an automation on a monday board from a structured natural-language description. It specifies the verb 'creates', the resource 'automation', and the context 'monday board' and 'structured natural-language description'. This distinguishes it from sibling tools like 'list_automations' and 'manage_automations'.

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

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

The description provides explicit guidance on when to use the tool: only when the agent knows boardId, the intended trigger, at least one action, and relevant details. It also states what the agent does not need to know (exact automation blocks) and advises asking for clarification if details are missing. However, it does not explicitly state when NOT to use the tool or mention alternative tools.

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

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

Annotations provide minimal info (non-read-only, non-destructive). Description adds nothing beyond 'create', failing to disclose permissions, quotas, conflict handling, or side effects. For a creation tool, this is insufficient.

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

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

One sentence with zero wasted words. Extremely concise and front-loaded with the verb and resource.

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

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

Given 5 parameters, no output schema, and many sibling tools, the description is too minimal. It omits return value, required context (e.g., workspaceId), and potential behaviors, making it incomplete for effective use.

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

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

Schema coverage is 100%, so the schema fully explains parameters. The description adds no extra meaning beyond the schema, meeting the baseline but not exceeding it.

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

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

The description 'Create a monday.com board' clearly states the action and resource. It distinguishes from sibling tools like create_item or create_column, which target different entities. However, it could be more specific about the board concept in Monday.com.

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

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

No guidance on when to use this tool vs alternatives or any prerequisites. The description provides no context for decision-making, leaving the agent without usage boundaries.

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

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

Annotations indicate mutating but non-destructive behavior. The description adds no extra context about effects on existing items, permissions, or reversibility.

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

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

The description is a single, efficient sentence that directly states the purpose. It is concise but could benefit from additional context without becoming verbose.

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

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

For a 5-parameter creation tool with no output schema, the description lacks information on return values, columnSettings usage (requires external API), and practical implications of column creation.

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

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

Schema coverage is 100% with clear descriptions for all parameters. The tool description does not add meaning beyond what the schema provides, justifying the baseline of 3.

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

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

The description 'Create a new column in a monday.com board' clearly states the action (create) and the resource (column), distinguishing it from sibling tools like create_item or create_board.

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

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

No guidance on when to use this tool versus alternatives such as update_column or delete_column. The description does not mention prerequisites or context.

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

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

Annotations indicate readOnlyHint=false (write operation) and destructiveHint=false. The description confirms it creates an activity, but adds no additional behavioral context such as required permissions, side effects, or what happens on success/failure. Given annotations already present, the description fails to provide extra transparency.

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

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

The description is a single sentence, very concise and to the point. However, it uses the abbreviation 'E&A' which may not be immediately clear to all agents. It is front-loaded but could be slightly clearer. Still, it earns high marks for brevity.

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

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

The tool has 3 required parameters all described in the schema, and no output schema. The description is minimal but covers the basic purpose. However, it lacks context about the E&A app, typical usage scenarios, or how the result is returned. For an agent, more completeness would help disambiguate from similar tools.

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

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

Schema coverage is 100%, with descriptions already provided for each parameter (color, icon_id, name). The description does not add any further meaning or usage guidance beyond what the schema offers. Therefore, the baseline score of 3 is appropriate.

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

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

The description clearly states the action ('Create') and the resource ('a new custom activity'). It is specific enough to convey the tool's function. However, it does not explicitly differentiate this tool from similar siblings like 'fetch_custom_activity' or other 'create_*' tools, so it falls short of a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical use cases, or exclusions. This is a significant gap for an AI agent deciding between tools.

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

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

Annotations show readOnlyHint=false and destructiveHint=false, so description correctly implies mutation. It adds context about data aggregation but does not disclose details like permissions or rate limits. No contradiction.

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

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

Four sentences, front-loaded with the main action, no redundant words. Every sentence serves a purpose.

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

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

Given the tool has 5 parameters and no output schema, the description covers creation purpose, board aggregation, and widget context. It lacks mention of return value but is sufficient for selection.

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

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

Schema description coverage is 100%, so all parameters already have descriptions. The tool description adds no param-specific information beyond what the schema provides, meeting the baseline.

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

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

Description clearly states the tool creates a monday.com dashboard that aggregates data from boards, with visual representations via widgets/charts. It distinguishes from siblings like create_board by specifying the aggregation purpose.

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

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

Description explicitly lists three usage scenarios (visualize board data, aggregate from multiple boards, set up visualization container) but does not directly mention when not to use or compare to alternatives.

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

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

Annotations indicate non-readonly, non-destructive, non-idempotent. The description adds behavioral details: creation is a mutation, markdown is appended, ownership is set via docOwnerIds bypassing permission checks. This exceeds annotation information.

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

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

The description is well-structured with sections for location types and usage examples. It is substantive and front-loaded, but could be slightly more concise (e.g., examples could be condensed). Still, it earns its place without excessive verbosity.

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

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

Given the complexity of 9 parameters with conditional requirements, the description covers both location scenarios thoroughly with examples and behavioral notes. It lacks mention of return value (e.g., doc ID), but this is minor and the description is otherwise complete.

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

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

Schema coverage is 100%, but the description adds value by grouping parameters by location, clarifying conditional requirements (e.g., 'use only when location="workspace"'), providing defaults (doc_kind defaults to public), and offering concrete usage examples. This goes well beyond the schema alone.

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

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

The description clearly states the verb 'Create' and specifies the resource 'monday.com doc' with two distinct location types (workspace or item). It distinguishes from sibling tools like 'update_doc', 'read_docs', and 'add_content_to_doc' by focusing on creation.

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

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

The description provides explicit guidance on when to use each location type, including required vs optional parameters per scenario. Usage examples illustrate typical input structures. However, it does not explicitly state when NOT to use this tool or mention alternatives like 'add_content_to_doc' for existing docs.

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

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

Annotations provide readOnlyHint=false and destructiveHint=false, but the description adds no additional behavioral context. It does not mention side effects, permissions, or what happens on success/failure. The description carries minimal value beyond the annotations.

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

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

The description is a single sentence, no wasted words, but could be expanded slightly to improve clarity without losing conciseness. It effectively conveys the core purpose.

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

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

No output schema, and the description does not explain return values, error behavior, or prerequisites (e.g., workspace existence, permissions). For a creation tool, critical context is missing.

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

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

Schema description coverage is 100% with all 6 parameters described. The tool description does not add any additional meaning or context for parameters beyond the schema, so baseline score of 3 is appropriate.

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

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

The description clearly states 'Create a new folder' (specific verb+resource) and specifies the context 'in a monday.com workspace'. Among sibling tools like create_board, create_group, etc., it effectively distinguishes itself.

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

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

No guidance on when to use this tool versus alternatives. With many sibling tools for creating other entities, the description lacks any comparison or usage context.

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

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

The description adds that creating a form also creates a backing board, which is not obvious from annotations. It also discloses the return of formToken. Annotations already indicate mutable action (readOnlyHint=false). The description enhances transparency.

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

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

Two sentences, front-loaded with the core purpose, and includes key behavioral context and return value. No unnecessary words.

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

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

With 9 parameters, low schema coverage, no output schema, and the complexity of creating a form with a backing board, the description is too brief. It fails to explain parameter interdependencies or potential failure modes.

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

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

Schema coverage is only 33% (3 of 9 parameters have descriptions). The description does not compensate by explaining any parameter meanings or relationships. Most parameters (e.g., destination_workspace_id, board_kind) remain undocumented.

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

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

The description clearly states the action ('Create a monday.com form'), the resource (a form), and the side effect (creates a backing board). It also mentions the return value (formToken). This distinguishes it from siblings like 'create_form_submission' and 'create_board'.

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

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

No guidance on when to use this tool versus alternatives (e.g., create_board, create_form_submission). No prerequisites or context for usage are provided.

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

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

Annotations indicate write operation (readOnlyHint false). The description adds value by detailing token resolution, the need to gather answers upfront, unsupported subitems, and the return of a submission ID. It does not contradict annotations.

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

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

The description is structured with a clear opening sentence followed by a bulleted list of steps. While detailed, every sentence adds value without redundancy. Slightly verbose but justified by complexity.

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

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

Given 5 parameters, 3 required, and no output schema, the description covers the workflow thoroughly, referencing get_form, explaining token handling, and noting unsupported subitems. It adequately prepares the agent for correct usage.

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

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

Schema coverage is 100%, but the description adds context beyond the schema, such as explaining the form_token URL formats, auto-resolution, and the requirement to gather all answers. It also clarifies the answers array structure and unsupported subitems.

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

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

The description clearly states 'Submit a response to a monday.com WorkForm.' It uses a specific verb (submit) and resource (WorkForm), and distinguishes itself from sibling tools like get_form and form_questions_editor by providing a detailed workflow.

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

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

The description explicitly instructs to 'Use get_form first' and 'Gather all answers upfront — do not submit one question at a time.' It also explains acceptable token formats and auto-resolution of shortened URLs, providing clear context for when and how to use the tool.

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

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

Describes creation behavior including positioning relative to groups and color assignment. Annotations show no destructive or readOnly hints, so description adds some value. Does not mention error cases or prerequisites but is adequate.

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

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

Four concise sentences, front-loaded with purpose, no redundancy. Every sentence adds value.

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

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

Covers the main use cases and parameter constraints. No output schema, but description doesn't need to detail return values for a straightforward creation tool. Could mention response, but not critical.

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

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

Schema coverage is 100% so baseline is 3. The description adds context about groups organizing items and the top group hint, which slightly enhances parameter understanding. No contradiction.

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

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

Clearly states the verb 'create' and resource 'group in a monday.com board'. Provides context about groups organizing items, and distinguishes from siblings like create_board or create_item.

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

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

Explicitly says 'Use when users want to add structure, categorize items, or create workflow phases.' Also gives a practical hint about the top group for new items. Lacks explicit when-not-to-use or alternative tools, but sufficient.

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

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

Annotations already indicate mutability (readOnlyHint=false). Description adds context about non-destructive creation and the prerequisite for board structure knowledge. No contradiction with annotations.

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

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

Four sentences, front-loaded with purpose, then parameter usage and prerequisite. Every sentence is essential and well-structured.

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

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

Covers the three modes and prerequisite well. Minor gap: no description of return value (e.g., created item ID) since output schema absent.

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

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

Schema coverage is 100%, baseline 3. Description adds value by explaining how to use parentItemId for subitems and duplicateFromItemId for duplication, and provides an example for columnValues beyond schema.

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

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

The description clearly states the tool creates items with three modes: new item, subitem under parent, or duplicate with modifications. It distinguishes from sibling tools like delete_item and change_item_column_values.

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

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

Explicit guidance on when to use parentItemId vs duplicateFromItemId, and a prerequisite to use get_board_info if unfamiliar with board structure. Clearly differentiates from other tools.

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

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

Annotations show readOnlyHint=false (write operation), destructiveHint=false (not destructive). The description adds that it sends via bell and optionally by email, which is useful context beyond annotations. No contradictions.

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

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

Two sentences covering core purpose and usage guidance. Front-loaded with action and channels. No unnecessary words.

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

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

The description covers purpose, channels, and target_type usage. However, it does not explain the return value or how to trigger the optional email (no parameter for email). This minor gap prevents a perfect score.

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

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

Schema coverage is 100%, but the description adds value by explaining target_type mapping ('Post' for updates/replies, 'Project' for items/boards). It does not elaborate on other parameters, but the schema already describes them adequately.

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

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

The description clearly states it sends a notification via bell icon and optionally email, distinguishing it from siblings like create_update. It specifies the target_type options, making the purpose very clear.

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

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

The description gives clear context on when to use (sending notifications) and how to use target_type. However, it does not explicitly state when not to use or mention alternatives, though no alternative notification tool exists among siblings.

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

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

The description indicates a creation action, consistent with readOnlyHint=false, but adds no additional behavioral context beyond what annotations imply. Missing details like required permissions, side effects, or reversibility.

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

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

The description is two sentences, front-loaded with the action, and contains no fluff. It is appropriately concise for a straightforward creation tool.

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

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

Given no output schema, the description should explain what the tool returns (e.g., the created schema object) but does not. It also lacks context about when to create an object schema, making it incomplete for an agent.

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

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

The input schema has 100% description coverage, so the parameters are already well-documented. The tool description adds no extra parameter-level information, so baseline score of 3 is appropriate.

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

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

The description clearly states the action ('Create') and the resource ('account-level object schema'), and it implicitly differentiates from siblings like update_object_schema and delete_object_schema. However, it could be more specific about what an object schema entails.

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

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

There is no guidance on when to use this tool versus alternatives, such as when to create a schema versus using manage_object_schema_columns. No prerequisites or context for usage are provided.

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

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

While annotations indicate the tool is not read-only, the description merely restates the creation action without disclosing any additional behavioral traits such as side effects, permissions required, or irreversible consequences. The description adds negligible value beyond the already evident write operation.

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

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

The description is a single, clear sentence with no extraneous information. It is appropriately sized and front-loaded with the action and resource.

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

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

Given the tool's complexity (11 parameters, no output schema), the description is too minimal. It fails to explain what a 'timeline item' is, how it relates to other items, or what the result of creation looks like. More context is needed for the agent to confidently use this tool.

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

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

The input schema has 100% description coverage, so the schema already documents all parameters. The tool description adds no parameter details. With full schema coverage, baseline score 3 is appropriate.

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

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

The description clearly states the action ('Create') and the resource ('a new timeline item'), and specifies the app context ('E&A app'). However, it does not distinguish this tool from similar sibling tools like 'create_item' or 'create_update', which may cause confusion about when to use this specific tool.

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

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or contexts. This omission leaves the agent without decision-making criteria for tool selection among many create_* siblings.

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

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

Annotations already indicate not read-only and not destructive; description adds context about mentions and replying but lacks details on side effects (e.g., notifications triggered) or permissions. Acceptable but not thorough.

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

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

Four sentences front-loaded with main purpose, then usage details. No fluff, every sentence adds value.

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

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

Covers essential aspects for a 4-param, 2-required tool with no output schema. Missing return value description, but otherwise complete for the task.

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

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

Schema covers all parameters (100%), and description adds extra value: explains that body should not use @, HTML formatting, mentions format, and parentId for replies. Significantly enhances understanding.

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

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

Clearly states the action 'Create a new update' and the resource 'on a monday.com item'. Distinguishes from siblings like create_item or create_notification by specifying it's for comments/posts.

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

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

Does not explicitly indicate when to use this tool versus alternatives like create_notification or add_content_to_doc. Provides parameter usage hints but no selection guidance.

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

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

Annotations are all false, and the description adds minimal behavioral context beyond the obvious creation action. It does not disclose side effects, permissions, rate limits, or return format.

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

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

The description contains unnecessary procedural instructions (calling full board data tool and show table tool) that are not part of the tool's core purpose, making it longer than needed.

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

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

With no output schema, the description should provide information about the return value, but it does not. It adequately covers parameter usage but lacks completeness in explaining the result.

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

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

Schema coverage is 100%, and the description adds a useful usage note about not using '@' and using mentionsList instead, which clarifies parameter behavior beyond schema definitions.

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

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

The description clearly states it creates an update (comment/post) on a monday.com item, but does not differentiate from the sibling tool 'create_update', which likely has a similar purpose.

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

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

No guidance on when to use this tool versus alternatives (e.g., 'create_update' or 'get_updates'). The description only includes post-call workflow instructions, not usage context.

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

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

Annotations are minimal (readOnlyHint=false, destructiveHint=false). The description adds that it creates a saved view and provides filter operator details. It does not discuss side effects (e.g., triggers, permissions) or response. It is adequate but not exhaustive.

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

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

The description is concise: four sentences covering purpose, filter operators, and two clear examples. It is front-loaded with the essential purpose and avoids fluff. Every sentence earns its place.

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

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

The tool has 6 parameters with nested objects and no output schema. The description explains filter operators and examples but omits sorting syntax and return value description. It is largely complete but could include a brief note about the response structure.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds value by listing common filter operators with examples and clarifying that settings for TABLE views should use create_view_table. This enhances parameter understanding beyond the schema.

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

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

The description clearly states 'Create a new board view (tab) with optional filters and sorting.' It identifies the resource (board view) and action (create). However, it does not explicitly differentiate from the sibling tool create_view_table, though the settings parameter hints at the distinction.

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

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

The description does not provide explicit 'when to use' or 'when not to use' guidance. It implies usage for creating saved views with filters/sorting, but lacks directive like 'prefer create_view_table for TABLE views' in the description itself (that appears only in the schema). No exclusion criteria are given.

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

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

Annotations indicate non-readonly and non-destructive. Description adds context about table-specific settings but does not mention permissions, naming conflicts, or side effects beyond creation. Adequate but leaves some unknowns.

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

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

Description is concise with two paragraphs and examples. Front-loaded purpose. Could be slightly more structured but overall effective.

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

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

No output schema but tool is create operation, likely returns success. Covers main aspects of complex tool with 6 parameters and nested settings. Lacks details on return value or async behavior, but sufficient for typical use.

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

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

Schema covers all parameters. Description provides examples for settings.columns and settings.group_by, and lists filter operators, adding significant value beyond the schema especially for complex nested objects.

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

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

Description clearly states it creates a 'table-type board view' with optional filters, sort, tags, and table-specific settings. Differentiates from sibling 'create_view' by specifying when to use this tool instead of create_view.

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

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

Explicitly recommends using this tool over create_view for table-specific settings and notes create_view works for simple table views, providing clear usage guidance.

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

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

Annotations are minimal (readOnlyHint false, destructiveHint false); description adds validation requirements and parent container context but does not discuss error handling or concurrency.

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

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

Well-structured with headings and bullet points, front-loaded purpose. Slightly longer than minimal but each section earns its place.

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

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

Covers workflow, prerequisites, parent container types, and settings validation. No output schema exists, but description sufficiently explains creation behavior.

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

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

Schema coverage is 100%, so baseline 3. The description reinforces the need for schema validation for 'settings' but does not add new semantic detail beyond schema descriptions.

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

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

Clear verb 'Create' and resource 'widget', specifies placement in dashboard or board view, differentiates from sibling tools like all_widgets_schema by describing workflow.

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

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

Explicitly states prerequisite use of all_widgets_schema, gives step-by-step workflow, and outlines critical requirements for schema compliance and validation.

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

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

Adds value beyond annotations by explaining return values (workflowObjectId, workflowDraftId), workflow lifecycle (drafts must be published), and terminology. No contradictions with annotations.

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

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

Front-loaded with purpose and usage, includes helpful terminology and UI note. Slightly verbose but every section adds value; could be trimmed slightly.

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

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

Covers return values, draft concept, alternative tools, and UI URL. Lacks permission/error details but appropriate for a creation tool.

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

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

Schema coverage is 100%, so baseline is 3. The description adds minor context (e.g., defaults, privacy descriptions) but does not significantly enhance parameter meaning beyond the schema.

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

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

Description clearly states 'Creates a new empty workflow' and distinguishes from sibling 'create_automation' by explaining workflows are standalone workspace-level objects.

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

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

Explicitly says 'Use this when the user wants to build a new standalone workflow from scratch' and contrasts with automations, providing strong usage guidance. Lacks explicit 'do not use' scenarios.

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

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

Annotations already provide readOnlyHint=false and destructiveHint=false. Description adds no behavioral context beyond what's implied by 'create', but does not contradict annotations.

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

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

A single sentence that is front-loaded and contains no wasted words. It effectively communicates the tool's purpose.

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

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

Without an output schema, the description should explain return values or success indicators. It also lacks prerequisites, error conditions, or other context needed for a creation tool with 4 parameters.

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

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

Schema coverage is 100% with descriptions for all 4 parameters. The description adds no additional meaning beyond the schema, meeting the baseline.

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

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

Description clearly states the action (create) and resource (workspace) and platform (monday.com). It is clear but does not differentiate from similar create tools like create_board or create_dashboard.

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

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

No guidance on when to use this tool vs alternatives like list_workspaces or update_workspace. The description only states what it does without context for choosing it over other tools.

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

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

Annotations already mark destructiveHint=true, and the description merely repeats the deletion action without additional behavioral context like irreversibility, impact on board data, or authorization needs.

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

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

The description is a single sentence with zero wasted words. It is front-loaded and earns its place.

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

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

Given the low complexity (2 params, no output schema) and annotations covering destructiveness, the description is essentially complete for an agent to understand the core action. Minor gaps exist but are not critical.

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

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

Schema coverage is 100%, but the description adds no parameter meaning. Moreover, the schema description for 'boardId' incorrectly says 'new column will be added', which is misleading for a deletion tool. The tool description does not correct this.

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

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

The description clearly states the action 'Delete' and the resource 'column from a monday.com board', with specific context. It does not explicitly differentiate from sibling tools like 'delete_item' or 'update_column', but the purpose is unmistakable.

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

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

The description provides no guidance on when to use this tool versus alternatives (e.g., 'update_column', 'create_column'). No context on prerequisites, such as ensuring the column exists or permissions required.

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

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

Annotations already indicate destructiveHint=true, so the agent knows it's destructive. However, the description does not elaborate on consequences, permissions, or any irreversible behavior beyond what annotations convey.

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

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

The description is very short, which is concise, but it lacks any structure or additional details. Every word is earned, but it could be more informative without being long.

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

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

Given the tool is a delete operation with a single parameter and no output schema, the description fails to mention return values, success/failure indicators, or error handling. It is minimally complete.

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

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

Schema description coverage is 0%, and the description does not explain the itemId parameter meaning, format, or constraints. The description adds no value beyond the schema.

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

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

The description 'Delete an item' clearly states the verb (delete) and resource (item), making it unambiguous. It is distinct from sibling tools like create_item or update_item.

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

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

No guidance on when to use this tool versus alternatives like move_item_to_group or update_... No prerequisites or exclusions mentioned.

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

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

Annotations indicate destructiveHint=true; description adds context about the prerequisite (no boards connected) and scope (account-level), going beyond the annotation alone.

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

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

Two sentences, no fluff, front-loaded with the action and condition. Every word serves a purpose.

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

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

Covers the main aspects: what it does, the prerequisite, and how to specify the target. Lacks mention of return value, but for a simple delete operation with annotations, this is sufficient.

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

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

Schema description coverage is 100%, so the schema already documents both parameters. The description adds 'Provide either id or name,' reinforcing mutual exclusivity but not providing new information.

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

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

Clearly states 'Delete an account-level object schema.' with a specific verb and resource, and the condition distinguishes it from other delete tools like 'delete_column' or 'delete_item'.

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

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

Provides a condition for when deletion is allowed (no boards connected) and instructs to provide either id or name. However, it does not explicitly mention when not to use this tool or suggest alternatives.

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

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

Annotations already indicate destructiveHint=true. The description adds context by stating 'Permanently delete' and the board-connection prerequisite, which clarifies the behavioral constraints beyond the annotations.

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

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

Two sentences, no redundant information. First sentence delivers the core purpose, second adds critical usage conditions and alternatives. Efficient and front-loaded.

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

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

For a tool with 3 parameters, no output schema, and clear annotations, the description is fully complete. It covers purpose, prerequisites, and alternatives, leaving no gaps.

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

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

Schema coverage is 100%, so the input schema already describes all parameters. The description reiterates the board-connection condition mentioned in columnIds, but does not add new meaning beyond the schema.

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

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

The description states 'Permanently delete columns from an account-level object schema,' clearly identifying the verb (delete), resource (columns from an object schema), and scope (account-level). It distinguishes from sibling tools like manage_object_schema_columns and set_object_schema_column_active_state.

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

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

Explicitly states when the tool can be used ('Only allowed when no boards are connected to the schema') and provides a reversible alternative ('Use manage_object_schema_column with action=deactivate'). This helps the agent choose correctly.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds no additional behavioral information beyond the purpose, such as whether results are paginated or limited.

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

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

Single sentence, no wasted words. Front-loaded with action and resource.

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

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

Given no output schema, the description does not explain the return format or structure. While simple, it could be more complete by stating what is returned.

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

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

Input schema is empty (no parameters), so schema coverage is 100%. Description adds meaning about source ('E&A app') but does not need to explain parameters.

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

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

The description clearly states the specific verb 'Get' and resource 'custom activities' from 'the E&A app'. It distinguishes from sibling tools like 'create_custom_activity' and other read tools.

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

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

No explicit guidance on when to use this tool versus alternatives. Since it has no parameters and is a simple fetch-all, usage is implied but not stated.

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

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

Annotations already indicate readOnly, non-destructive, idempotent. The description adds behavioral details beyond annotations: supported file types, return formats per type, truncation behavior with has_more/next_offset, and that images return a public URL. No contradictions.

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

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

Well-structured with clear sections: purpose, proactive use, supported types, response details, usage criteria. Every sentence adds value and is appropriately positioned. Length is justified by complexity.

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

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

Despite having no output schema, the description comprehensively explains return values (text content, total_length, has_more, next_offset, or public URL for images). All parameters are covered with usage context. Complete for the tool's functionality.

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

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

Schema descriptions cover all parameters (100% coverage). The description adds meaning by explaining how to obtain item_id and column_id from get_board_items_page, the purpose of file_name hint for ambiguous types, and offset for truncation handling.

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

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

The description clearly states the verb 'fetch' and the resource 'text content from a file stored in a monday.com files column'. It distinguishes from sibling tools by specifying when to use it for reading file contents, as opposed to other read tools like get_board_items_page.

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

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

Provides explicit 'When to use' and 'When NOT to use' sections, including proactive usage guidance. The description gives clear context for when this tool should be selected over alternatives.

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

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

The description adds significant behavioral context beyond annotations: it outlines the required sequence (call after get_asset_upload_url, need etag from PUT response), confirms the create action, and mentions automatic attachment. No contradictions with annotations (readOnlyHint=false, destructiveHint=false).

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

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

Two sentences with no unnecessary words. The first sentence states the core purpose, and the second provides essential workflow details. Efficient and front-loaded.

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

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

The description covers the return value (asset_id) and the overall workflow. However, it lacks details on error conditions (e.g., invalid etag) or idempotency, which would be helpful for a multi-step process. Given no output schema, it is mostly complete.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining how uploadId and etag relate to the presigned URL process and that columnId is the target for attachment. This extra context justifies a score of 4.

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

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

The description clearly states the tool's purpose: 'Finalize a file upload and create the asset on monday.com.' It distinguishes itself from siblings by explicitly referencing the prerequisite step (get_asset_upload_url) and the need to upload the file first, making its role in the workflow unambiguous.

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

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

The description explains when to use the tool: after uploading to the presigned URL and obtaining the etag. It mentions automatic attachment to a file column, but does not explicitly state when not to use it or provide alternative tools. However, the context is clear enough for correct invocation.

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

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

The description aligns with annotations (destructiveHint=true) by stating create/update/delete actions. However, it adds no additional context about side effects, required permissions, reversal possibilities, or data integrity concerns (e.g., preserving option values for existing submissions). The schema’s options field does provide some guidance, but the description itself is minimal.

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

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

The description is a single, efficient sentence that immediately conveys the tool’s purpose. It is front-loaded and free of redundancy, earning a high score for conciseness. However, it could be slightly more descriptive without losing brevity.

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

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

Given the tool’s complexity (nested objects, many parameters, no output schema), the description is too brief. It lacks details about return values, how to properly update options (though the schema mentions calling get_form first), or error handling. The description alone does not sufficiently inform an agent about the full behavior and requirements.

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

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

Schema description coverage is high (75%), and the schema already contains detailed descriptions for each parameter (e.g., action enum, question object fields). The description's brief summary does not add meaningful insight beyond the schema, so it meets the baseline of 3.

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

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

The description clearly states the tool performs create, update, or delete operations on questions within a monday.com form. It uses specific verbs and a distinct resource ('question in a monday.com form') that distinguishes it from sibling tools like create_form or update_form, which handle the form itself.

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

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

The description provides no guidance on when to use this tool versus alternatives such as get_form (for reading questions) or update_form (for form-level changes). It does not mention prerequisites or context, leaving the agent to infer usage solely from the action parameter.

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

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

Annotations already provide readOnlyHint, destructiveHint, idempotentHint. The description adds context beyond annotations: public URL expiration (1 hour) and the full list of metadata fields returned. No contradictions.

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

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

The description is two sentences, front-loaded with the action and resource, and every sentence provides valuable information without redundancy or fluff.

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

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

Given the tool's simplicity (one parameter, no output schema), the description fully explains what the tool does and what it returns. All relevant information for an agent to invoke it correctly is present.

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

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

The single parameter 'ids' has a schema description, and schema coverage is 100%. The description does not add new parameter-specific details beyond the schema, but it is adequate given the high coverage.

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

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

The description clearly states the verb 'Get' and the resource 'assets (files)', and lists specific metadata returned. It distinguishes from sibling tools like 'finalize_asset_upload' or 'get_asset_upload_url' by focusing on retrieval by IDs.

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

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

The description implies use when you need file metadata by IDs, but does not explicitly state when not to use it or mention alternative tools for other operations. No exclusion criteria provided.

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

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

Beyond annotations (readOnlyHint=false, destructiveHint=false), the description adds workflow context: the tool returns upload_id and upload_url, and guides the user on how to use the URL and capture the ETag. It also mentions the 500MB limit. No contradictions with annotations.

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

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

The description is front-loaded with the purpose and provides a clear workflow. It includes a useful curl example, but is slightly verbose. Overall well-structured and concise.

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

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

The description is comprehensive: it explains the return values, how to use the URL, the follow-up tool (finalize_asset_upload), and a constraint (max file size). For a tool with 3 parameters and no output schema, it covers all essential context.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context by explaining the role of contentType in the curl command and reinforcing the fileSize limit. This adds meaning beyond the schema's type descriptions.

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

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

The description clearly states the tool's purpose: to get a presigned URL for uploading a file to monday.com. It distinguishes from sibling tools like finalize_asset_upload by providing the initial step in a two-step workflow.

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

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

The description provides explicit instructions on when to use this tool (to obtain an upload URL) and the subsequent steps (upload with curl, then call finalize_asset_upload). It mentions max file size but does not explicitly state when not to use it or mention alternatives.

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

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

Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds mode behaviors, pagination details, scope constraints, and known states (success, failure, exhausted). Does not cover auth or rate limits, but that's acceptable given annotations.

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

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

Well-structured with clear sections (modes, scope, known states). Every sentence adds value without redundancy. Concise but information-dense.

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

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

No output schema, but description adequately explains return values: paginated run feed with state/duration/error for history, block steps and tool calls for detail. Covers all required and optional parameters.

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

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

Schema already has 100% description coverage. The description adds valuable context on pagination (nextPageOffset = previous offset + returned count) and default behavior (includeToolEvents defaults true). Enhances understanding beyond schema.

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

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

Clearly states it reads automation/workflow run history, with two distinct modes (history and detail) that differentiate the tool from siblings. The verb 'read' and resource 'automation/workflow run history' are specific.

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

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

Provides clear guidance on mode selection, filtering, pagination (offset-only), and scope (boardId vs accountWide). However, it does not explicitly compare to alternative tools like get_board_activity or get_updates.

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

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

Annotations already mark it as read-only and idempotent; the description confirms 'Read-only' and adds behavioral details about breakdowns and required parameters. No contradictions.

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

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

Five sentences front-loaded with purpose, structured with bullet-like lists for breakdowns. Every sentence adds value; no redundancy.

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

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

Given no output schema, the description covers the tool's essential quirks (breakdown types, scope, optional filters). Could mention response structure, but not critical for a statistics tool.

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

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

Schema coverage is 100%, but the description adds valuable context, such as requiring one of boardId/accountWide, clarifying the runStatus dependence on breakdown, and explaining excludeAutomationIds usage.

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

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

The description clearly states it aggregates automation run statistics, with a specific verb ('aggregate') and resource ('automation run statistics'). It distinguishes itself from sibling tools like 'get_automation_runs' and 'manage_automations' by focusing on statistics and breakdowns.

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

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

The description provides clear context on when to use each breakdown type and scope (board vs. account-wide). It doesn't explicitly name alternatives, but the purpose and parameter details guide appropriate use.

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

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds value by specifying the default time range, advising against fetching entire board data without filters, and warning that includeData payloads can be very large. This exceeds what annotations provide.

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

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

Two concise sentences: first states the core function and default, second explains key filtering options. Every word serves a purpose, no fluff, and the most important information is front-loaded.

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

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

The description covers essential aspects: purpose, default behavior, filtering options, and a warning about large data. While it does not explicitly describe return format or pagination, the schema and annotations sufficiently cover the tool's safety and idempotency. Overall, it is complete for effective use.

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

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

Schema coverage is 100% with detailed descriptions for all parameters. The description adds broad guidance (e.g., 'defaults to last 30 days') but does not provide new meaning beyond what the schema already conveys. Baseline score of 3 is appropriate.

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

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

The description clearly states that the tool retrieves board activity logs for a specified time range, with optional filtering by item or user IDs. This distinguishes it from sibling tools like get_board_info or get_board_schema, which serve different purposes.

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

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

The description provides guidance on when to use filters ('to avoid fetching activity for the entire board') and mentions default behavior (last 30 days). It lacks explicit exclusions or comparisons to alternatives, but the context is clear enough for most use cases.

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

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

Annotations already indicate readOnlyHint and idempotentHint. The description adds value by detailing return content (views with id, name, type, filter object) and confirming comprehensive nature, without contradicting annotations.

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

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

Two sentences, front-loaded with main purpose, no fluff. Every word contributes to clarity.

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

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

With no output schema, the description provides a useful summary of return data (metadata, views). Could be more exhaustive (e.g., permissions), but adequate for a single-parameter read-only tool.

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

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

Schema coverage is 100% with a clear description for the single parameter 'boardId'. The description does not add extra meaning or examples beyond the schema, so baseline 3 is appropriate.

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

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

The description uses a specific verb 'Get' and resource 'comprehensive board information', listing included elements (metadata, structure, owners, configuration, views). This clearly distinguishes it from sibling tools like 'get_board_items_page' or 'get_board_schema'.

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

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

No explicit guidance on when to use this tool versus alternatives such as 'get_full_board_data'. The description implies usage by stating its scope, but lacks when-not-to-use or direct comparisons.

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

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

Discloses pagination behavior (nextCursor, has_more), optional includes, and performance tips. Annotations already indicate read-only and non-destructive. Description adds practical usage details without contradicting annotations.

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

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

Well-structured: main purpose first, then prerequisites, then view-filtering. Somewhat long but each sentence adds value. Could be slightly more concise, but effective.

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

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

No output schema, but description explains response structure (timestamps, pagination info) and parameter usage. Covers all needed aspects for a read-only paginated tool, given the rich annotations.

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

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

All 13 parameters have schema descriptions. The description adds context like when to enable includeItemDescription and performance optimization for columns. While schema coverage is high (baseline 3), the extra context justifies a 4.

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

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

The description clearly states it gets items from a monday.com board with pagination and optional fields. It uses specific verb 'get' and resource 'items from a board', distinguishing it from siblings like get_board_info and get_full_board_data.

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

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

Includes explicit prerequisites: use get_board_info for unfamiliar board structure or new columns, and link_board_items_workflow for cross-board tasks. Also provides guidance for view-based filtering and performance optimization. Lacks explicit 'when not to use' but covers key scenarios.

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

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

Annotations already provide readOnlyHint=true and idempotentHint=true. The description adds no additional behavioral context (e.g., error handling, rate limits, or what happens on invalid board ID).

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

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

The description is a single sentence with no extraneous words. It could include more detail without becoming verbose.

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

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

Given no output schema, the description should indicate the structure of the returned schema (e.g., fields of columns/groups). It mentions 'columns and groups' but lacks detail, leaving the agent underinformed about what to expect.

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

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

Schema coverage is 100% and the description matches the parameter. It adds minimal meaning beyond the schema's existing description of boardId.

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

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

The description clearly states it retrieves board schema (columns and groups) by board ID. It uses a specific verb and resource, distinguishing it from siblings like get_board_info or get_board_items_page.

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

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

The description implies when to use it (when schema is needed) but does not provide explicit when-not or alternatives among related tools like get_column_type_info or get_object_schemas.

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

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

Annotations declare readOnlyHint and idempotentHint. The description adds behavioral detail about the two modes (e.g., 'no GraphQL round-trip' for guidelines) and their specific outputs, enhancing transparency beyond annotations.

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

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

The description is concise (two sentences) and front-loaded with the purpose, then details each mode efficiently without redundancy.

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

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

Given no output schema, the description adequately explains what each mode returns (JSON schema vs. guidelines.filter/aggregation) and covers all necessary context for a tool with two simple enum parameters.

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

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

Input schema covers all parameters with descriptions. The description elaborates on fetchMode's two options and their practical purposes, adding value beyond the schema enumeration.

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

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

The description clearly states it retrieves comprehensive information about a specific column type, distinguishing two fetch modes for different use cases. This differentiates it from sibling tools like create_column or get_board_schema.

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

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

Explicitly advises using fetchMode 'schema' before creating/updating columns and fetchMode 'guidelines' for building filters/aggregation, providing clear when-to-use context without needing alternatives.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by explaining how to derive the formToken, a behavioral instruction not covered by annotations.

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

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

Three sentences: first sentence states purpose, remaining two concisely explain parameter extraction. No wasted words, front-loaded with key action.

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

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

For a simple one-parameter retrieval tool with no output schema, the description is complete. It explains the parameter and implies the return value (the form object). No gaps remain.

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

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

Schema coverage is 0%, so description fully compensates by clearly explaining the formToken parameter, its format, and how to extract it from a URL, which is essential for correct usage.

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

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

Clearly states the verb "Get" and resource "monday.com form by its form token", distinguishing it from sibling tools like create_form or update_form.

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

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

Provides detailed instructions for extracting the formToken from a URL, but does not discuss when to use this tool versus alternatives like form_questions_editor or get_form_submission.

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

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds the crucial behavioral context that the tool is exclusively triggered by UI components, beyond what annotations convey. No contradictions.

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

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

The description is a single imperative sentence that effectively conveys the key restriction. It is concise, but could be structured with bullet points for clarity. The urgency of the prohibition justifies brevity.

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

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

Given that the tool is explicitly forbidden for agent use, the description is complete in conveying that it should not be called. However, it does not describe return value or behavior when called, which would be necessary if the agent were allowed to use it. The lack of output schema is not compensated.

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

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

Schema description coverage is 100%, with detailed descriptions for each parameter (boardId, filters, filtersOperator). The tool description does not add further parameter-level information, so the baseline score of 3 is appropriate.

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

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

Explicitly states the tool is for internal UI use only, clearly distinguishing it from other board-related tools that the agent should use instead. The purpose is unambiguous: it provides full board data but is not for agent invocation.

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

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

Provides explicit guidance to never call the tool directly, but does not mention alternative tools like get_board_items_page or get_board_info that could serve similar purposes. The strong prohibition is clear but lacks cross-references.

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

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

Annotations already declare readOnly and idempotent hints. The description adds useful details like scanning recently used boards (up to 100) and the need for manual input if none found, providing behavioral context beyond annotations.

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

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

The description is concise and well-structured with clear sections (Purpose, What it Returns, Note). Every sentence adds value without redundancy.

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

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

Given no output schema, the description adequately explains the return structure (pairs of board IDs, names, workspace info) and includes important context about the scan limit and fallback procedure. It covers the essential edge case of no boards found.

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

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

The tool has zero parameters, and schema coverage is 100%. According to guidelines, no parameters yields a baseline of 4. The description does not need to add parameter info.

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

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

The description clearly states the tool discovers sprints boards and tasks boards, specifying what it returns. However, it does not explicitly differentiate from similar sibling tools like get_sprints_metadata or get_sprint_summary, which might also return board information.

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

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

The description indicates the tool is a prerequisite for other monday-dev tools and notes the scan limit and fallback, but it lacks explicit guidance on when not to use it or how it compares to alternatives.

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

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

Annotations already indicate readOnlyHint, destructiveHint, and idempotentHint. The description adds behavioral context such as the large size of transcripts and pagination support, enhancing transparency without contradicting annotations.

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

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

The description is concise, front-loads the purpose, and efficiently covers all key parameters in two sentences without redundancy.

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

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

Given 9 parameters, no output schema, and high schema coverage, the description adequately covers pagination, defaults, and parameter usage. It lacks return format details but that's acceptable without output schema.

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

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

Schema coverage is 100% with detailed parameter descriptions. The description adds value by grouping flags and explaining how to use them together (e.g., controlling details), and clarifying access level defaults.

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

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

The description clearly specifies the verb 'Retrieve' and the resource 'notetaker meetings' with optional detailed fields. It distinguishes itself from sibling tools by focusing on notetaker meetings, which is a specific domain not covered by other tools.

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

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

The description provides clear context on filtering by access, IDs, search, and pagination, and defaults to OWN. It doesn't explicitly state when not to use or alternatives, but the context is sufficient given no direct sibling for this resource.

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

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

Annotations indicate readOnly/ idempotent; description adds context about account-level schemas and pagination, but doesn't cover potential errors or unusual behavior.

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

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

Three sentences, each adding value, starting with purpose, then definition, then usage. No wasted words.

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

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

Describes purpose, filtering, and pagination. Lacks return structure details, but given readOnlyHint and no output schema, it is nearly complete for a retrieval tool.

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

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

Schema coverage is 100%. Description adds minimal usage context for ids/names (mutually exclusive) but does not enhance understanding of limit, page, or excludeCreatedByMonday beyond the schema.

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

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

The description clearly states the verb 'Retrieve' and the resource 'account-level object schemas', specifies filtering by IDs or names, and distinguishes from sibling tools like create/delete/update_object_schema.

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

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

The description explains when to filter vs list all (paginated), but lacks explicit guidance on when not to use this tool or alternatives (e.g., for modifying schemas).

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds the output data fields but does not disclose additional behavioral traits such as permissions, error handling, or rate limits. It provides adequate but not rich behavioral context beyond annotations.

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

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

The description is well-structured with clear sections and front-loaded information. It is concise but includes a list of output fields that could be partially inferred from the schema, though still helpful. No waste, but slightly verbose.

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

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

Despite no output schema, the description lists the data retrieved, making the return values clear. It mentions the required board ID and limit parameter. However, it does not address pagination or multiple boards, but given the sibling for board IDs, it is sufficiently complete for a metadata retrieval tool.

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

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

Schema coverage is 100%, and the schema descriptions already cover both parameters. The description repeats the limit default and max but adds no new meaning beyond what the schema provides. Baseline 3 is appropriate.

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

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

The description uses a specific verb ('Get') and resource ('comprehensive sprint metadata from a monday-dev sprints board'), clearly distinguishing it from siblings like get_monday_dev_sprints_boards (which returns board IDs) and get_sprint_summary (which returns summary of a single sprint).

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

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

The description states that the tool requires the 'Main Sprints board ID' but does not explicitly guide when to use this tool versus alternatives. It implies usage context but lacks explicit when-not or alternative tool references, which are available among siblings.

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

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

Annotations already indicate read-only and idempotent. Description adds constraints (must be completed) and output format details (user IDs), adding value beyond annotations without contradiction.

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

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

Well-structured with sections (Purpose, Requirements, Important Note) and bulleted content. No unnecessary sentences, though slightly long. Front-loads the core purpose.

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

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

Covers the return content, prerequisites, and a usage hint. No output schema, so description sufficiently explains what to expect. Could detail output format more but adequate for agent use.

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

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

Input schema already describes sprintId (100% coverage). Description adds valid value constraints (completed sprint, after 1/1/2025), improving parameter understanding beyond schema.

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

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

Clearly states 'Get the complete summary and analysis of a sprint' and lists specific content categories (scope, velocity, etc.). However, it does not explicitly differentiate from sibling tool get_sprints_metadata.

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

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

Provides prerequisite (sprint must be completed, created after 1/1/2025) and a useful note on handling user IDs with list_users_and_teams. Lacks explicit when-not-to-use or alternatives but gives clear context.

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

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

The description adds behavioral context beyond the readOnlyHint annotation by detailing return data (text, creator info, timestamps, optional replies/assets) and default behavior for Board queries (only board discussion). No contradiction with annotations.

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

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

The description is three sentences, front-loaded with purpose and usage, no unnecessary words. It efficiently covers core functionality, filters, and return values.

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

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

Given 9 parameters and no output schema, the description adequately covers most aspects: object types, filtering, item updates inclusion, and return content. It lacks explicit pagination behavior but provides enough context for an agent to use the tool effectively.

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

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

The input schema has 100% coverage, so baseline is 3. The description adds value by explaining the conditional usage of fromDate/toDate (both required, ISO8601) and includeItemUpdates (only for Board, default false).

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

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

The description clearly states the tool retrieves updates (comments/posts) from a monday.com item or board, specifying the resource and context. It distinguishes from sibling tools like 'create_update' by focusing on retrieval.

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

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

The description provides clear guidance on required parameters (objectId, objectType) and optional filters (date range, includeItemUpdates). It explains when to use fromDate/toDate together and the effect of includeItemUpdates, though it does not explicitly mention alternatives.

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