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

Although no annotations are provided, the description discloses the initial status and the return of a 'slug' for referencing. It explains the semantics of each parameter, but lacks information on auth requirements or side effects beyond creation.

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 clear summary first, then parameter details. It is slightly verbose but each section adds value, and the bullet-point format aids readability.

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 high parameter count (12) and no output schema provided, the description covers most aspects well, including return value (slug) and parameter semantics. It could mention the full response structure, but it is largely 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 coverage is 0%, so the description bears the full burden. It provides detailed explanations, format examples (e.g., 'scope: <layer>-<tech>', 'due_date: ISO-8601'), and special guidance for fields like 'acceptance_criteria', 'constraints', and 'context_pointers', significantly aiding 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?

The description clearly states the verb 'Create' and the resource 'dev-task', and specifies that new tasks start at status '待评估'. This distinguishes it from sibling tools like update_dev_task or get_dev_task.

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 when-to-use or when-not-to-use guidance is provided. While the purpose is clear, there is no mention of alternatives or context that would help an agent decide between this and sibling 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?

Describes response contents (spec fields, dependency info, slug) and explains context_pointers short-circuits file discovery. No contradictions with annotations (none provided).

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 action, response details, parameter info. No fluff. Front-loaded with essential 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?

Output schema exists, so return description not needed. Covers purpose, parameter format, usage guidance, and response contents. Fully sufficient for a fetch-by-ID 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 description coverage is 0%, but description explains task_id as 'ObjectId hex string (24 hex chars)' and directs to alternative tool for slugs, adding meaning 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?

Explicitly states 'Fetch a single dev-task by its ObjectID.' Distinct from sibling 'get_dev_task_by_slug' which uses slug.

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?

Directly tells when to use this tool (when you have ObjectID) and when to use alternative (slug). Provides usage advice: read spec fields, use context_pointers.

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?

With no annotations, the description carries the burden of behavioral disclosure. It mentions the result is the same as 'get_dev_task', implying it is a read operation, but does not explicitly confirm read-only nature or disclose any side effects, rate limits, or error conditions.

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

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

The description is concise and front-loaded with the primary function. It uses efficient language, though the bilingual mix (English and Chinese) may slightly reduce clarity for some users.

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 tool (1 required parameter) and presence of an output schema, the description covers purpose, parameter usage, and relationship to sibling 'get_dev_task'. It lacks explicit error handling or edge-case documentation, but is overall 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 has 0% description coverage, but the description adds meaning by providing an example format ('task-42') and context explaining that slug is a human-readable short identifier. This compensates for the lack of schema 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 'Fetch a single dev-task by its slug', using a specific verb and resource. It distinguishes from sibling 'get_dev_task' by specifying the use of slug instead of ID, and explains the slug's advantage over ObjectID.

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 that slug is a human-readable short identifier better for oral references, kanban UI, and MCP conversations, guiding when to use this tool over alternatives. However, it does not explicitly state when not to use it or provide alternative tools by name.

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?

With no annotations provided, the description carries the burden. It explains the frontier conditions, ordering (sort_order ASC, then created_at DESC), and that tasks are not soft-deleted. It stops short of mentioning auth or rate limits, but for a read tool this 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?

The description is concise, front-loaded with the main purpose, and every sentence adds value. It uses bullet points for clarity and ends with an Args line. 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?

Given the tool's complexity (filtered list with four conditions) and the existence of an output schema, the description covers all essential aspects: what it does, when to use, criteria, ordering, and parameter. The agent can fully understand how to invoke it 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?

The only parameter, 'limit', is described as 'Max tasks to return (default 10).' The schema provides type and default, but the description adds context on its purpose. Schema coverage is 0% because no inline schema, but the description compensates.

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 returns tasks the agent can claim next, specifically the 'frontier', and defines the four criteria that constitute the frontier. It distinguishes from sibling tools by focusing on ready-to-work 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 explicitly says 'Use this as your first call when the user says "do the next task"', providing clear guidance on when to use. It does not mention when not to use, but the positive instruction is strong.

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?

With no annotations, the description carries the full burden. It discloses filter parameters, pagination (page, per_page with a cap of 20), and flags for agent and deleted tasks. While it doesn't mention sorting or result structure, the output schema exists to cover return values. Overall, the description provides reasonable behavioral insight.

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 statement and then lists each parameter with explanations. It is somewhat lengthy but contains no redundant information. The structure is clear and easy to parse.

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 7 parameters and the presence of an output schema, the description covers all parameter semantics thoroughly. It does not mention expected response format or ordering, but the output schema likely provides that. The description is sufficient for an agent to 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 0%, so the description adds essential meaning beyond the schema. It explicitly lists all enum values for status, priority, and task_type, explains the boolean filters for_agent and include_deleted, and clarifies pagination constraints. This adds significant value for correct invocation.

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 ('List dev-tasks') and the resource ('your kanocifer-chat board'). It is distinct from sibling tools like create, get, update, etc., providing a specific verb+resource combination.

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 explicitly state when to use this tool versus alternatives like get_dev_task or get_frontier_tasks. However, the name 'list' implies retrieval of multiple items, and the detailed filters suggest it's for filtered aggregation. No exclusion or alternative guidance is 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?

With no annotations, the description discloses the partial update behavior. It explicitly notes for blocked_by that the list is replaced entirely and can be cleared with []. No mention of authorization or side effects, but for a straightforward update, this is sufficient.

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 organized as a docstring with an Args list, front-loading the core behavior. It is somewhat lengthy due to the number of parameters, but each line is necessary given the schema lacks descriptions. It could be slightly more concise but remains clear.

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 15 parameters and a required one, the description covers all parameters with enough detail. There is an output schema, so return values don't need explanation. No explicit error handling or prerequisites, but it's adequate for a partial update 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 0%, so the description fully compensates by listing each parameter with meaningful descriptions, including enum values for task_type, priority, and status. It provides additional details like 'slug (task-N)' for task_id and 'replace the dependency list entirely' for blocked_by.

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 'Partially update a dev-task' with a specific verb and resource. It distinguishes from sibling tools like create_dev_task, get_dev_task, and list_dev_tasks, as update is the only mutation tool for existing 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 explains that omitted fields are left unchanged, implying a PATCH-like usage. It doesn't explicitly state when to use this tool versus alternatives, but the context of siblings makes it clear. The list of parameters indicates that only task_id is required, guiding the agent on minimal input.

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