Dida365 MCP Server

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Server Quality Checklist

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Latest release: v0.2.2
Disambiguation5/5
Each tool targets a distinct resource (project, task, auth) and action (create, read, update, delete, list), with no overlapping purposes. Auth tools are clearly separated from task operations.
Naming Consistency5/5
All tools use a consistent verb_noun pattern in snake_case (e.g., create_project, list_tasks, revoke_auth), making it easy to predict functionality from names.
Tool Count5/5
15 tools cover the full lifecycle of projects and tasks plus authentication support, without unnecessary redundancy. The count is well-scoped for a task management MCP server.
Completeness5/5
The surface includes CRUD for projects and tasks, batch operations, filtering, and auth flow. No obvious gaps—core workflows are fully supported.
Average 4.6/5 across 15 of 15 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. Mentions return value (project with ID) and that ID is needed for subsequent tasks. Does not disclose side effects, permissions, or idempotency. Adequate 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (WHAT, WHEN, REQUIRED, OPTIONAL, RETURNS). Concise, no wasted words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complexity: 5 params, 1 required, enums, output schema. Description covers usage, param details, and return value. Lacks mention of validation errors or edge cases, but sufficient for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value with Chinese translations, examples for color and viewMode, and explanation of sortOrder. Enhances usability beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (create), resource (project), and purpose (organizing tasks). Distinguishes from sibling tools like create_task by specifying it creates a list/folder/project.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a 'WHEN TO USE' section with explicit scenarios (new task list, folder, organizing categories). Does not explicitly state when not to use or suggest alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes a read-only operation but does not mention potential behaviors like pagination, rate limits, or auth beyond implicit user context. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with purpose sentence, bulleted usage, return list, and tip. Every sentence adds value; no wasted words. Front-loaded key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and an output schema, the description fully covers return fields (id, name, color, etc.) and provides actionable tip linking to sibling tools, making it complete for the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in input schema (schema coverage 100%). Per rule, baseline 4 for 0 params. Description does not add parameter info but correctly indicates no input needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve all projects for the current user' with specific verb and resource. It distinguishes from siblings like 'get_project' (single) and 'get_project_data' (complete data) via the usage section and tip.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'WHEN TO USE' section provides clear use cases: overview, finding project ID, checking metadata. Lacks explicit when-not-to-use but tip suggests alternatives like 'get_project_data' for complete data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers behavioral traits: batch updates are non-atomic with failed checks, auto-mapping of description based on task type, and the side effect of task becoming CHECKLIST when items provided. It lacks auth or rate limit info but is adequate for a task update tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (WHEN TO USE, REQUIRED, OPTIONAL, INPUT FORMAT, BATCH BEHAVIOR) and bullet points. Slightly verbose but front-loads essential info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers most aspects for a complex batch update tool: input format, batch behavior, required/optional fields, and key behaviors. Missing details on error handling beyond failed count, batch size limits, and return structure (no output schema). Could add what the response contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds bilingual labels, practical notes (auto-mapping of description, date format examples, priority values), and explains conditional behavior like 'items' making task a checklist. This goes well beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool updates one or more existing tasks and supports batch updates. It uses a specific verb and resource, and distinguishes from sibling tools like complete_task by including batch behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'WHEN TO USE' section lists specific modification scenarios (title, description, dates, priority, sub-tasks) and required parameters. It also explains batch non-atomicity. However, it does not explicitly state when not to use or compare with alternatives like complete_task, missing a bit of guidance for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Although no annotations exist, the description discloses key behavioral aspects: response fields (content, desc, kind, items). It explains the distinction between TEXT and CHECKLIST tasks and includes a note about unified description parameter mapping. Missing explicit statement of read-only nature, but overall good transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (general, WHEN TO USE, WHEN NOT TO USE, REQUIRED, RESPONSE FIELDS, NOTE). All sentences add value. Slightly verbose but organized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get tool, the description is very complete. It covers purpose, usage guidelines, required parameters, response fields, and special behavior (TEXT vs CHECKLIST). With output schema existing, no further detail needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds Chinese translations and restates required parameters, but does not add substantial new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve detailed information about a specific task', using a specific verb and resource. It distinguishes from siblings like list_tasks and get_project_data in the WHEN NOT TO USE section.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides WHEN TO USE and WHEN NOT TO USE sections, naming alternatives and giving clear context for when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation ('check auth status') and appropriate usage context. While no annotations exist, the behavioral intent is clear. Could explicitly state no side effects, but the check nature is transparent enough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose. Each sentence adds value: when to use, when to avoid, and scope. Could be slightly tighter, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an output schema present, the description adequately covers usage guidelines and context. It specifies the limited domain (Dida365 MCP authorization) and avoids over-explaining return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. The description adds no parameter info, but none is needed. The baseline of 3 is appropriate, and the description provides usage context that compensates for any potential ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks authorization status and specifies when to use it (user asking about authorization, deciding if protected operations can proceed). It distinguishes from sibling tools like get_auth_url and revoke_auth by focusing on status checking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides conditions for use (user asks about authorization, unclear status before protected operations) and when to avoid (if status already known in current turn). Also restricts scope to Dida365 MCP authorization context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses partial update behavior, required projectId, and optional parameters. It does not cover permissions, reversibility, or potential side effects, but for a simple update tool 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with headings and bullet points, each section concise and valuable. No redundant 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.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, 1 required) and 100% schema coverage, the description is complete. It covers usage, partial update, and parameter details. Output schema exists but its content is not needed for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning by grouping fields (required/optional), providing Chinese translations, and clarifying the 'at least one required' constraint. Examples for color and sortOrder further aid understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Update an existing project's settings' and lists specific use cases (rename, change color, view mode, type, reorder). It distinguishes from siblings like create_project and delete_project through context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a 'WHEN TO USE' section with explicit scenarios, partial update behavior, and required vs optional parameters. It does not explicitly state when NOT to use it or mention alternatives like create_project, but the sibling list and context signals provide implicit differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses batch non-atomicity, return summary for failures, and the note about inbox projectId transformation. It also describes side effects (creation of tasks) but could be more explicit about authentication requirements (though auth tools are siblings). Overall, it provides substantial behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear headings, bullet points, and bilingual support. It is somewhat lengthy but every section serves a purpose given the complexity. Front-loading the core function and required fields helps quick understanding. Minor redundancy in examples, but overall efficient for its depth.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description covers key behavioral details: non-atomic batch, failure check, inbox projectId handling. It doesn't describe full return fields but mentions summary structure. Given the complexity (batch, nested items), it is sufficiently complete for an agent to use correctly. Could add more about successful return format, but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant value: priority value-to-label mapping, reminder trigger format examples, repeatFlag RRULE syntax, description auto-mapping, and the critical projectId vs inbox distinction. It also explains items array creating CHECKLIST type. This goes well beyond what the schema alone provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates one or more tasks in a project, with batch support. It explicitly contrasts with sibling tools like update_task, complete_task, and delete_task by specifying its create-only function. The verb 'Create' combined with resource 'task(s)' and context 'in a project' makes the purpose precise and distinguishable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
A dedicated 'WHEN TO USE' section lists specific scenarios. The 'INBOX VS PROJECT' detail provides explicit guidance on when to use each, including rules and examples. This clearly differentiates from siblings and prevents misuse. The description also notes when batch creation is appropriate and how to handle failures.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses destructiveness (irreversible), idempotency (deleting non-existent returns success), and batch non-atomicity, meeting the full burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections and warnings, every sentence adds value, and it is front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While no output schema exists, the description mentions response fields like 'summary.failed' and covers batch behavior and idempotency. Minor gap on full response structure, but highly complete for a destructive batch tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptions for both parameters. The description restates but adds no new semantic information 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool deletes tasks with specific verb and resource, and distinguishes it from sibling tools like complete_task by specifying when not to use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'WHEN TO USE' and 'WHEN NOT TO USE' sections provide clear guidance, including alternatives like complete_task and noting archive is unsupported.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Warns that the action is destructive, irreversible, and deletes all tasks within the project, fulfilling behavioral disclosure in the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections and warnings, concise and front-loaded with critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a simple delete tool with one parameter; output schema likely covers return values, and usage guidance is thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3 applies. Description adds emphasis but no new semantic detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool permanently deletes a project and all its contents, distinguishing it from sibling tools like delete_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
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 alternative tool (update_task) for moving tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that it provides a time-limited URL and starts a local callback server. Could mention token storage but not essential for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no wasted words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an output schema likely describing the return, the description covers the tool's purpose, usage context, and key behavioral details (time limit, callback server). Complete for the task.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so baseline is 4. No information needed beyond what the schema already provides (empty schema).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's purpose: to provide an authorization URL when OAuth errors occur or user requests reauthorization. It explicitly distinguishes from siblings by specifying it's not for generic OAuth.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (authorization errors, user requests) and when not to use (not for generic OAuth). Provides context about URL validity (≈10 min) and the callback server mechanism.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description fully covers behavior. Clearly states return value (project metadata only) and what it excludes (tasks). Implies read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections. Every sentence adds value, no redundancy. Concise yet informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple single-parameter tool and existence of an output schema, the description is complete. It specifies what is returned and what is not, aligning with typical usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with description for projectId explaining it's the unique ID. Description adds context 'by ID' but does not add significant value beyond schema. Baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Retrieve metadata for a single project by ID', providing a specific verb and resource. It distinguishes from siblings like get_project_data and list_tasks by clarifying scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit WHEN TO USE and WHEN NOT TO USE sections with clear alternatives (get_project_data, list_tasks). Provides precise guidance on when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description fully carries behavioral transparency. Discloses limitation that only uncompleted tasks are returned and completed tasks are inaccessible. Mentions return structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections, front-loaded main purpose, no wasted sentences. Length appropriate for complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description provides sufficient context about return data (project, tasks, columns). Covers all relevant behavioral aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'projectId' already well-documented. Description adds Chinese terms but does not significantly enhance understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly specifies the verb 'Retrieve', resource 'complete project data', and lists sub-resources. Distinguishes from sibling tools like 'get_project' and 'list_tasks' through explicit when-to-use guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
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 with specific scenarios and alternative tools (e.g., 'get_project' for metadata, 'list_tasks' for filtered tasks). Clearly states limitation about completed tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses key behaviors: idempotency (completing already-completed or non-existent returns success), that completed tasks are hidden from list/get tools, and non-atomic batch execution.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections, emoji highlights, and no redundant information. Every sentence adds value despite being longer than minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, parameters, and behavioral notes. However, it lacks a description of the return output structure (beyond mentioning 'summary.failed'), which would be helpful for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for projectId and taskId. The description adds the required input format, clarifies Chinese terms, and provides context on usage, going beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool marks one or more tasks as completed, supports batch completion, and distinguishes from siblings like delete_task and update_task in the WHEN NOT TO USE section.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit WHEN TO USE (user finished a task, batch complete) and WHEN NOT TO USE sections, naming specific alternatives (delete_task, update_task) and noting idempotent behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the key limitation that only uncompleted tasks are returned, and explains sorting and filtering behavior. No annotations exist, so the description fully covers behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections and bullet points, making it easy to scan. However, it is somewhat lengthy and contains some redundancy with the schema, which could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is comprehensive: it covers usage, exclusions, quick filters, optional filters, sorting, a limitation, and examples. Given the tool's complexity (8 optional params, no required), this is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are already documented. The description adds value by including Chinese translations, examples, and clarifying use cases for presets, but some repetition exists.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists and filters tasks across projects. It uses specific verbs ('List and filter tasks') and distinguishes from sibling tools like get_project_data and get_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'WHEN TO USE' and 'WHEN NOT TO USE' sections with direct references to alternatives (get_project_data, get_task). This provides clear guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: 'Clears stored tokens and stops any running authorization server; user must re-authorize afterward.' This informs the agent of destructive effects and required re-authorization. No annotations exist, so the description carries full burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the first sentence front-loading the primary usage condition. Every sentence adds value, no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and the presence of an output schema (though not shown), the description covers when to use, behavior, and consequences thoroughly. It is complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and schema coverage is 100%. The description adds context about the tool's purpose and effect beyond the empty schema. Baseline is 4 for no parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'revoke, reset, clear, or remove Dida365 authorization/tokens'. It specifies the verb and resource, and distinguishes from sibling tools by contrasting with token refresh and generic OAuth logout.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use ONLY when the user explicitly requests...' and provides specific scenarios (log out, revoke, reset, clear, remove, or cancel pending authorization). It also includes negative guidance: 'Do NOT call for token refresh, generic OAuth logout of other services, or routine task operations.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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