nudge

Server Quality Checklist

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Latest release: v1.0.2
Disambiguation4/5
Tools are mostly distinct but check_tasks and search_todos overlap in searching, and list_todos with filters overlaps with get_pending_today and get_stats, causing mild ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun snake_case pattern (e.g., create_todo, mark_complete), making them predictable and easy to distinguish.
Tool Count5/5
With 8 tools, the set is well-scoped for a task management assistant, covering core operations without being overwhelming.
Completeness4/5
The set covers CRUD operations except for task deletion, and lacks editing capabilities, but the core lifecycle (create, read, update status) is present.
Average 3.9/5 across 8 of 8 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
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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 provided, so description carries full burden. Only states it lists with filters, with no disclosure of read-only nature, return format, or side effects. Agents lack important behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, directly front-loaded with action and filters. No wasted words; every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 optional parameters, no output schema, and no annotations, the description is too sparse. It omits details on default behavior (e.g., returns all tasks if no filters), ordering, or pagination, leaving agents underinformed.
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 80%, so description does not need to add much. The description merely says 'optional filters', adding no extra meaning beyond what the schema already provides for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'List the user's tasks with optional filters', which specifies the verb and resource. Does not explicitly differentiate from siblings like search_todos or get_pending_today, but the primary purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Says 'Use this when asked directly, or when you need context to give a useful, honest answer about where things stand', which provides some usage context but no exclusions or comparisons with alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It lacks disclosure of behavioral traits such as case sensitivity, exact matching, pagination, or whether it returns only matching tasks. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero wasted words. Every word earns its place.
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?
For a simple tool with one parameter, the description is adequate but could mention output or search behavior. Lacks details like return format or search algorithm, but schema and simplicity keep it minimally complete.
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% with a clear description for 'query'. The tool description adds no additional meaning beyond what the schema provides. Baseline score 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 action (search) and the scope (task titles and notes by keyword). It distinguishes from sibling tools like list_todos which lists all tasks without filtering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 check_tasks or list_todos. The description only states what it does, not when it's appropriate or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description alone must disclose behavioral traits. It only states the creation action and hints at confirmation, but omits important details like side effects, idempotency, permissions, or error handling.
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 very concise: two sentences plus usage examples, all front-loaded and to the point. Every sentence adds value, avoiding any fluff or redundancy.
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?
Given 5 parameters, no output schema, and sibling tools, the description covers when to use and what to do after, but lacks explanation of return values (e.g., what 'confirm' means) or error scenarios, making it slightly incomplete for a creation 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?
Schema description coverage is 100%, so the schema already documents all parameters well. The description adds no new parameter information beyond the usage examples, which slightly reinforces the schema but does not significantly enhance 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 'Add a new task to the user's list' with specific verb and resource. It provides concrete usage examples and distinguishes from sibling tools (e.g., list_todos, mark_complete) 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.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use the tool ('when user says remind me...') and advises confirming the action. However, it does not mention when not to use it or suggest alternative sibling tools for different scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It implies read-only behavior but does not explicitly state side effects, permissions, or rate limits. The hint about "gentle mention" adds some context but insufficient detail for complete transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero wasted words. The purpose is front-loaded and the use case follows immediately. Every sentence earns its place.
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?
For a simple tool with no parameters and no output schema, the description covers the purpose and a usage scenario. However, it lacks detail on the exact return value (list of tasks? counts?) and how it differs from list_todos. Some gaps remain for full 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?
The tool has zero parameters, and schema coverage is 100%. The description does not need to explain parameters, and it adds no conflicting information. Baseline 4 is appropriate for a no-parameter tool.
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's function: "See what's still on the user's plate for today". It uses a specific verb-noun pair (see pending tasks) and differentiates from siblings like list_todos by focusing on today's items. The use case (mid-day or end-of-day check-in) adds specificity.
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 explicitly advises using this tool for "natural mid-day or end-of-day check-in" and hints at agent behavior ("worth a gentle mention"). However, it does not explicitly state when not to use it or compare to alternatives like list_todos or check_tasks.
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?
Discloses fuzzy matching and that it checks completion status. No annotations provided, so description carries burden. Lacks details on behavior for non-existent tasks or multiple matches, but adequate 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, zero waste. Purpose is front-loaded. Efficient and clear.
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 low complexity (1 param, no output schema), description covers key aspects: purpose, matching behavior, typical use case. Could mention return format but not essential.
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?
Only one parameter 'names' with 100% schema coverage. Description reinforces fuzzy matching but adds limited new semantics beyond schema. 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?
Clearly states it checks whether specific things have been done, with fuzzy matching. Distinguishes from sibling tools like search_todos and list_todos by emphasizing the checking intent.
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?
Explicitly describes when to use: when user mentions something they said they'd do and want to see if it's on the list and ticked off. Provides example usage. Lacks explicit when-not-to-use but context with siblings implies it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states that it marks a task as done and suggests celebrating, but does not disclose potential side effects (e.g., irreversible action? requires write permissions?), prerequisites, or how task state changes. Minimal behavioral context beyond the obvious.
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, each front-loaded with key info: purpose, usage trigger, and a brief behavior note. The celebration remark is slightly extraneous but harmless. No filler, but could be tightened.
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 simple mutation tool with 2 parameters and no output schema, the description covers the core use case, when to use it, and how to resolve ambiguity. It does not describe return values, but that is acceptable given the lack of output schema. Minor missing info on success/failure indicators.
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%, and the description adds significant value: it explains the purpose of each parameter (id vs name for fuzzy-matching) and suggests using check_tasks to find the correct ID. This goes beyond the schema's own 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?
The description clearly states 'Mark a task as done' and provides specific trigger phrases (done, finished, crossed that off). It explicitly distinguishes itself from sibling tools like mark_incomplete and gives context for when to use it.
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 guidance is given (user says completion phrases) and a pre-step is recommended (fuzzy-match with check_tasks). It does not explicitly mention when not to use, but the positive guidance is clear and actionable.
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 are provided, so the description carries the burden. It states the tool reopens a task, which is a simple state change. The behavior is straightforward and adequately disclosed.
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 the main action. No unnecessary words. Every sentence adds value.
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 output schema, two simple parameters, and sibling tools, the description is complete: it explains the action, when to use, and parameters are fully described in the schema.
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 clear descriptions. The tool description adds minimal parameter info beyond the schema, only reinforcing usage context. 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 reopens a task marked done, using a verb and resource. It includes example user utterances to clarify intent. It distinguishes from the sibling tool 'mark_complete' which does the opposite.
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 explicitly says 'Use when the user says something like...' providing practical usage context. It implicitly distinguishes from alternatives but does not explicitly state when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly states that the tool returns a summary of counts (total tasks, done today, pending, overdue), which is transparent for a read-only aggregation tool. No side effects or additional behavior is needed given the simplicity.
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 with no wasted words. The first sentence immediately states the purpose and key outputs, and the second provides use-case guidance. It is front-loaded and 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 the tool's simplicity (no parameters, no output schema), the description covers the essential information. It provides enough context for the agent to know when to use it versus siblings. However, it could more precisely define terms like 'done today' (e.g., tasks completed today vs. created today).
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?
The tool has zero parameters, so the schema is fully covered (100%). The description adds value by explaining the nature of the output without needing to detail any inputs. This exceeds the baseline requirement.
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 verb 'Get' and the resource 'summary of where things stand', listing specific data points (total tasks, done today, pending, overdue). This distinguishes it from siblings like list_todos (which lists individual tasks) and get_pending_today (which focuses on pending tasks only).
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 explicitly recommends using this tool for 'an end-of-day check-in or when the user wants the big picture,' providing clear usage context. However, it does not mention when not to use it or name alternative tools explicitly, though the purpose differentiation is implied.
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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