mcp-task-tools
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: todo_manager for CRUD, priority_sorter for frameworks, time_estimator for duration, burndown_calculator for sprint metrics, standup_generator for reports. No overlap or ambiguity.
Naming Consistency5/5All tool names follow a consistent 'domain_verb' pattern (e.g., burndown_calculator, priority_sorter, todo_manager). The naming style is uniform with snake_case and predictable suffixes.
Tool Count5/5Five tools is well-scoped for a task management server offering core functions (CRUD, prioritization, estimation, sprint tracking, standup). No tool seems extraneous or missing.
Completeness4/5The tool set covers full task lifecycle (CRUD), prioritization, estimation, burndown, and standups. However, story points for burndown and subtask support for estimation are not explicitly tied into todo_manager, leaving minor gaps.
Average 3.8/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes input methods but does not disclose output behavior (e.g., whether tasks are reordered, returned with scores, or grouped). This lack of transparency could confuse an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that effectively conveys three method options and their requirements. It is front-loaded and concise, though could benefit from bullet points for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two required parameters and full schema coverage, the description is adequate but missing return value information. As there is no output schema, the description should explain what the tool returns (e.g., sorted list, scores) to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for each parameter and their method-specific fields. The description adds a high-level summary but does not provide meaningful extra detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's core purpose: 'Sort and prioritize tasks using proven frameworks'. It lists three specific frameworks (Eisenhower, RICE, MoSCoW), distinguishing it from sibling tools like standup_generator or time_estimator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for prioritization tasks but does not provide explicit guidance on when to use this tool vs alternatives, nor does it specify criteria for choosing among the three methods.
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?
Without annotations, the description carries the burden. It discloses that the tool computes ideal vs actual burndown, velocity, and forecast, suggesting read-only calculation. However, it does not confirm side effects (e.g., if it stores data) or mention permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundant words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description does not describe the return format or structure of the burndown data, velocity, or forecast. This leaves ambiguity for a complex calculation output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have descriptions in the schema (100% coverage), so the baseline is 3. The description adds context that parameters relate to burndown calculation but does not enhance syntax or format details beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate sprint burndown chart data' with specific outputs (ideal vs actual burndown, velocity metrics, completion forecast). It distinguishes from sibling tools like priority_sorter and standup_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (tasks with story points and sprint duration) but does not explicitly state when to use this tool vs alternatives like time_estimator or todo_manager. No when-not or exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It notes 'in-memory' and 'persistent within session', which adds value, but does not disclose behavior beyond schema (e.g., side effects, error handling, auth needs). Behavior is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundant information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 9 parameters and no output schema, the description should explain return values. It covers core actions and filtering but omits the structure of results, leaving agents uncertain about what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context about filtering but does not explain parameter relationships or usage beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool manages an in-memory task list and lists specific operations (add, complete, update status, delete, list). It distinguishes from sibling tools like burndown_calculator, which are analytical, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for basic CRUD on tasks but does not explicitly state when to use this tool versus alternatives. No guidance on exclusions or prerequisites is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the tool generates a standup update from the task list, implying a read operation, but does not explicitly disclose side effects, authentication needs, or limitations. The behavior is implied but not fully detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary function, and contains no redundant information. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, no output schema), the description adequately explains what the tool does and the structure of its output. It misses details like behavior when no tasks exist, but is largely complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'lookback_hours' is fully described in the schema (100% coverage), so the description does not add new meaning. Baseline is 3 per rubric.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a daily standup update from the current task list, specifying the three sections (yesterday, today, blockers) and the data source (todomanager). This is specific and distinguishes it from sibling tools like priority_sorter and burndown_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it's for generating standups, but does not explicitly compare to siblings or provide exclusions. However, the context is clear that it's used for daily progress reporting, and no misleading guidance is given.
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 carries full burden. It clearly indicates the tool is a computational estimator (non-destructive) and describes return values. However, it does not mention authentication, rate limits, or whether it modifies any state. For a calculation tool, this is acceptable 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences effectively convey purpose, methodology, inputs, and outputs. No redundant information; every phrase contributes meaning. The structure is front-loaded with the core action and follows with essential details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description adequately mentions return values. It covers key parameters and methodology. However, it could briefly note that estimates should be positive numbers or that the PERT formula is used, but this is minor. Overall, it is sufficiently complete for a tool with moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing baseline. The description adds context about PERT methodology and configurable buffer, which enhances understanding beyond field descriptions. It explains the purpose of optimistic/realistic/pessimistic estimates and the buffer parameter, adding value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates task duration using PERT methodology, specifying inputs (subtasks with optimistic/realistic/pessimistic estimates) and outputs (weighted expected time plus buffer). It distinguishes itself from sibling tools like burndown_calculator or priority_sorter by focusing on time estimation rather than tracking or sorting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for estimating task durations with PERT but does not explicitly state when to use this tool versus alternatives or provide exclusions. It lacks guidance on prerequisites or scenarios where this tool is inappropriate.
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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