digeguigui

Server Quality Checklist

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Latest release: v0.1.2
Disambiguation5/5
Each tool targets a distinct function: statistics, valuation, genetics, species profile, health diagnosis, image identification, trait search, name search, and provenance verification. No overlap in purpose.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern (e.g., genetics_calculator, search_by_traits) without mixing conventions or styles.
Tool Count5/5
With 9 tools, the server covers a broad range of reptile/pet management tasks without being excessive or inadequate for the domain.
Completeness4/5
The tool set covers search, identification, health, genetics, valuation, statistics, and provenance. Minor gaps like a species comparison tool are not essential for core functionality.
Average 3.7/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 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 should disclose behavioral traits. It only states a formula and does not explain side effects, idempotency, auth requirements, or return behavior. The agent lacks information on whether this is a read operation or what the output looks like.
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 a single concise line with no redundancy. However, it lacks structural elements like sections or bullet points. For a simple tool with a clear formula, this is efficient but could be improved.
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?
The tool has no output schema, and the description does not specify the return format (e.g., a number, currency, range). With three parameters and a formula, the agent needs to know what value to expect. The description is too sparse to be 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% for all three parameters. The description adds a formula that explains how parameters relate, but no additional per-parameter semantics beyond what the schema already provides. 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 explicitly states '价值预估' (value estimation) and provides the formula '基础价+品系基因溢价×品级系数', clearly indicating the tool computes an estimated value based on species, genes, and grade. This is distinct from sibling tools like genetic_calculator or search_by_traits.
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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when not to use it, or typical scenarios. The formula is given but without context for selection.
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 full burden. It states the tool shows statistics but does not disclose whether it is read-only, any rate limits, or the nature of the operation. Minimal behavioral disclosure beyond the stated scope.
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?
Single sentence with an emoji, front-loaded with the main 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should specify return format. It lists coverage areas but does not describe how results are presented (e.g., JSON with counts, string table). Moderate completeness given zero complexity.
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 (schema coverage 100%), so baseline is 4. The description adds value by listing the specific domains covered, overriding the need for further clarification.
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 provides a panoramic statistical overview of species, lineages, genes, prices, and image coverage, using a specific verb and resource. It is distinct from sibling tools which focus on specific domains like value estimation or genetics.
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 explicit guidance on when to use this tool versus alternatives like search_species or get_species_profile. The description implies a broad overview use, but does not state when not to use it or mention alternative tools.
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 behavioral burden. It does not disclose output format, response structure, or limitations beyond the schema's limit parameter. The description lacks details on pagination, sorting, 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 a single, front-loaded sentence with no wasted words. It conveys the core purpose and key capabilities efficiently.
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 the tool's simplicity (3 optional params, no output schema), the description covers search types and group but omits information about return format, error behavior, or result ordering. It is somewhat complete but lacks finishing details.
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 67%, so baseline is 3. The description adds context for q (supported search types) and group (examples), but fails to mention the limit parameter. It does not fully compensate for the missing schema description.
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 searches for reptile species, listing supported search types (Chinese name, Latin name, common names, group). This distinguishes it from siblings like get_species_profile or identify_turtle.
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?
The description implies usage for searching species but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. The guidance is implicit rather than explicit.
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?
The description discloses what the tool returns (breed, birth time, Git hash) but does not mention side effects, authentication needs, or error conditions. Since no annotations are provided, the description carries the full burden and is only partially transparent.
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 that efficiently conveys purpose and return data. No wasted words.
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?
The tool has one parameter and no output schema. The description lists three return items but does not specify their format or structure, leaving some ambiguity about the exact output.
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?
The schema covers 100% of the parameter with a clear description. The tool description only restates the parameter ('input anchor ID') without adding new semantic information 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's action ('verify pet ID') and specifies the return data (breed, birth time, Git hash). It distinguishes from sibling tools like get_species_profile or identify_turtle, which 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, nor does it mention prerequisites 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. The description only states the general search functionality without disclosing behavioral traits such as result format, pagination, filtering logic (AND/OR), or authentication requirements. For a search tool, these details are important.
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 sentence with an example, concise and front-loaded. Every part is essential and there is no redundancy.
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 8 parameters, no output schema, and no annotations, the description is insufficient. It does not explain search semantics (e.g., how parameters are combined), result structure, or limitations. Missing context for an agent to use it correctly without additional assumptions.
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 high (88%). The description adds an example of combining parameters, but does not provide additional meaning beyond what each parameter's schema description already conveys. Baseline score of 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's function: searching species by breeding conditions like 'beginner-friendly, small, aquatic, below 25°C'. This distinguishes it from sibling tools like search_species (name-based) and get_species_profile (by ID).
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 implies use when querying by multiple conditions, but does not explicitly contrast with siblings or specify when not to use it. However, the purpose is clear enough for an agent to infer 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?
The action verb '获取' (get) implies a read-only operation, and the description lists the data categories returned. While annotations are absent, the description is sufficiently transparent about the tool being a retrieval with no side effects.
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?
Single line in Chinese, front-loads the main purpose, and efficiently enumerates key data categories. Every part is necessary and informative.
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 retrieval tool with no output schema, the description covers the main content areas (classification, parameters, price, etc.). Lacks specification of output format but sufficient for basic understanding.
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 species_id described as '品种ID'. The tool description adds no additional meaning beyond the schema, so baseline score of 3 applies.
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 retrieves a complete species profile and lists specific content areas (classification, husbandry parameters, price, etc.), making the purpose unambiguous and distinguishing it from siblings like search_species which likely return summaries.
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 explicit guidance on when to use this tool vs alternatives like search_species or identify_turtle. The usage context is implied but not stated, leaving the AI to infer without exclusion criteria.
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 the description carries full burden. It discloses the basic behavior: input symptoms, output diagnosis with cause, treatment, prevention. However, it does not mention any limitations (e.g., only common diseases, confidence level, error handling for unrecognized symptoms), nor does it state whether the operation is read-only or safe. The transparency 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that includes the emoji for quick visual scanning, the action (symptom diagnosis), an example input, and the output structure. No unnecessary words; every part serves a 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?
Given the tool's simplicity (2 parameters, no output schema), the description adequately covers purpose, input format, output content (cause, treatment, prevention), and species scope. However, it does not mention any constraints like 'common diseases only' or that it's for educational purposes, which would improve completeness.
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 both parameters already described in detail (symptoms with examples, category with species list). The description reinforces these examples but adds no new semantic information beyond what the schema provides. Per guidelines, baseline is 3 when schema coverage is high, and the description does not elevate it.
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 it is a symptom diagnosis tool for reptile pets, matching input symptoms to common diseases and returning cause, treatment, and prevention advice. It provides an example symptom and specifies the covered species (turtles, snakes, lizards, frogs), distinguishing it from sibling tools that focus on genetics, identification, or statistics.
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 implicitly tells when to use (when you have symptoms to diagnose) without explicit alternatives or when-not-to-use. Given the clear purpose and distinct sibling tools (e.g., genetics_calculator, identify_turtle), the usage context is clear enough, but it lacks explicit guidance on limitations such as not replacing professional veterinary advice.
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 bears full responsibility for behavioral disclosure. It reveals that the tool uses AI, returns species and confidence, and has a direct conclusion threshold at 70% confidence. This adds useful context beyond the schema. However, it does not mention error handling, auth requirements, or limitations (e.g., need for clear turtle image).
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 extremely concise—two sentences in Chinese. It front-loads the purpose and immediately states the key behavioral rule (confidence threshold). Every word serves a purpose, with no fluff or redundant information. This is an ideal length for quick comprehension.
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 lack of output schema and annotations, the description does a good job covering the core functionality: it specifies the input format (turtle image base64), the output (species + confidence), and a key behavioral rule (direct conclusion at ≥70%). Missing elements include error handling (e.g., poor image, no turtle detected) and any rate limits, but these are acceptable gaps for a simple tool. The description is fairly complete for its complexity.
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 schema describes the parameter 'image_base64' as a base64 string. The description adds the semantic context that the image should be of a turtle ('龟类图片'), which is critical for correct invocation. With 100% schema coverage, the baseline is 3, and the description provides additional meaning beyond the schema, justifying a 4.
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 purpose: identifying turtle species from an image using AI, with confidence scoring. The verb '拍照识龟' (take photo to identify turtle) and the mention of 'AI识别品种+置信度' specifically convey the action and output. It is distinct from sibling tools like get_species_profile or search_species, which handle different operations.
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?
The description does not provide explicit guidance on when to use this tool versus alternatives, such as 'use get_species_profile for known species details'. The intended use case (image-based identification) is implied, but no when-not-to-use or alternative references are given. The threshold behavior (confidence ≥70%) offers some usage context, but lacks comprehensive guidelines.
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, but description clarifies it's a read-only calculator producing a table. Does not mention limitations, error handling, or data persistence. Supported inheritance types are disclosed, adding value.
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?
Single sentence with emoji, efficiently communicates purpose and supported features. No wasted words.
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?
No output schema, so description should detail return structure. Only says 'probability table', lacking format or explanation. Missing edge cases, species database behavior, and error handling. Adequate but not fully informative.
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 has 100% coverage with clear descriptions for each parameter. Description adds context on supported inheritance types and mentions optional species for gene database loading, 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?
Description explicitly states function: input parental genotypes, output offspring probability table. Lists supported inheritance types (dominant/recessive/codominant/multiple genes). No sibling genetics tools exist, so no confusion.
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?
Implies use for genetic cross calculation, but lacks explicit guidance on when to use or prerequisites (e.g., valid gene names, format). Since no alternative genetics tools exist, the impact is minor.
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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