Calorie-Tracking
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: logging meals, retrieving daily summaries, generating weekly reports, and searching food data. There is no overlap in functionality, making it easy for an agent to select the right tool without confusion.
Naming Consistency5/5All tools follow a consistent verb_noun naming pattern (e.g., add_meal, get_daily_summary, get_weekly_report, search_food). This uniformity enhances readability and predictability for agents using the toolset.
Tool Count5/5With 4 tools, the server is well-scoped for calorie tracking, covering core operations like logging, daily and weekly summaries, and food search. Each tool earns its place without being excessive or insufficient for the domain.
Completeness4/5The toolset covers essential CRUD-like operations for calorie tracking, including logging and retrieval. A minor gap exists in update or delete functionality for logged meals, but agents can likely work around this for basic tracking needs.
Average 2.7/5 across 4 of 4 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 Apache 2.0.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'Get[s]' a report, implying a read-only operation, but doesn't address permissions, rate limits, data freshness, or error conditions. For a tool with zero annotation coverage, this leaves significant behavioral gaps, though it doesn't contradict any annotations.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool, though it could be more front-loaded with critical details like parameter guidance, which would improve its utility without sacrificing brevity.
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?
Given the tool's moderate complexity (one parameter, no output schema, no annotations), the description is incomplete. It lacks details on parameter usage, behavioral traits, and differentiation from siblings, making it inadequate for an agent to confidently invoke the tool. The absence of an output schema means the description should ideally hint at return values, but it doesn't.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter ('startDate') with 0% description coverage, meaning the schema provides no details about its purpose or format. The description doesn't mention this parameter at all, failing to compensate for the schema's lack of documentation. This leaves the agent guessing about how to use 'startDate' effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get weekly calorie consumption report' clearly states the verb ('Get') and resource ('weekly calorie consumption report'), providing a basic understanding of what the tool does. However, it doesn't differentiate from sibling tools like 'get_daily_summary' or 'search_food' beyond the 'weekly' vs 'daily' distinction, leaving ambiguity about scope and overlap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'get_weekly_report' over 'get_daily_summary' or 'search_food', nor does it specify prerequisites, exclusions, or contextual triggers for usage, leaving the agent without operational direction.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a logging operation, implying data creation/mutation, but doesn't address permissions, side effects, error handling, or response format. This is inadequate for a mutation tool with zero annotation coverage.
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 a single, efficient sentence with no wasted words. It's appropriately sized for a simple tool and front-loads the core purpose without unnecessary elaboration.
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?
Given the tool's mutation nature, lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover behavioral aspects like what happens after logging, error cases, or how to interpret results, making it insufficient for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'food items and calories', which partially maps to the 'description' parameter, but doesn't explain 'mealType' or provide details on format, constraints, or how parameters relate to each other. This leaves significant gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Log') and resource ('a meal'), and mentions what data is involved ('with food items and calories'). However, it doesn't explicitly differentiate from sibling tools like 'search_food' or 'get_daily_summary', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'search_food' for looking up food items or 'get_daily_summary' for viewing logged meals. There's no mention of prerequisites, context, or exclusions, leaving usage unclear.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it indicates this is a read operation ('Get'), it doesn't address important behavioral aspects like whether authentication is required, what format the summary returns, if there are rate limits, or what happens when no data exists for the specified date.
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 extremely concise at just 5 words, front-loading the essential purpose without any unnecessary elaboration. Every word earns its place, making it efficient for quick understanding.
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?
For a tool with no annotations, no output schema, and undocumented parameters, the description is insufficiently complete. It doesn't explain what the summary contains, how it's formatted, whether authentication is needed, or how to interpret the optional date parameter, leaving significant gaps for an agent trying to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for its single parameter 'date', and the tool description provides no information about this parameter. The mention of 'today's' in the description might imply a default behavior when no date is provided, but this isn't explicitly stated, leaving the parameter's purpose and format completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('today's calorie intake summary'), making it immediately understandable. However, it doesn't explicitly distinguish this tool from its sibling 'get_weekly_report', which suggests a similar reporting function but for a different time period.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_weekly_report' or 'search_food'. It mentions 'today's' which implies a specific time context, but doesn't clarify if this is the only valid usage or if the optional 'date' parameter allows historical queries.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool searches for calorie information, implying a read-only operation, but doesn't cover aspects like rate limits, error handling, or response format. This is a significant gap for a tool with zero annotation coverage.
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 a single, efficient sentence with no wasted words, clearly front-loading the core purpose. It's appropriately sized for a simple tool, making it easy to parse quickly.
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?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, parameter usage, and output expectations, making it inadequate for reliable agent invocation without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description doesn't add any parameter details beyond implying 'foodName' is needed. It doesn't explain what constitutes a valid food name (e.g., formatting, examples) or constraints, failing to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Search for') and resource ('calorie information of a specific food'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_daily_summary' or 'get_weekly_report', which might also involve food data but serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a food name, or contrast with siblings like 'add_meal' for logging or 'get_daily_summary' for aggregated data, leaving the agent to infer usage context.
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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