bearing-local-business
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct concern: business profile, menu, availability check, and inquiry submission. There is no functional overlap between any pair of tools.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern: check_, submit_, get_, get_. The verbs are specific and the pattern is uniform.
Tool Count5/5With only 4 tools, the set is tightly scoped to the server's purpose of providing business info and handling custom-order inquiries. Each tool earns its place.
Completeness5/5The tool surface covers the core domain: discovering the business (profile), exploring offerings (menu), verifying order feasibility (availability), and initiating an order (inquiry). No essential operation is missing for the stated demo scope.
Average 4.1/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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
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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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: 'This is a demo: nothing is persisted or transacted' is a critical, non-obvious behavioral disclosure that prevents an agent from expecting real persistence. It also mentions the return of a reference. However, it does not describe validation behavior or the reference format.
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 short sentences, front-loads the purpose, and wastes no words. The demo warning is a necessary addition and is placed effectively. Every sentence contributes meaningful information.
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?
The tool has four parameters, no output schema, and no annotations, so the description is the only source of guidance. It explains the demo side effect and that a reference is returned, but it does not clarify parameter semantics, response structure, or when this is appropriate relative to sibling tools. This is insufficient for reliable invocation beyond a trivial case.
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 does not compensate by explaining any of the four parameters. While names like 'name', 'contact', and 'details' are self-explanatory, the optional 'date' field and expected formats or semantics are left completely unspecified, adding little beyond the schema's property list.
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 action: 'Capture a demo custom-order inquiry' and the output: 'return a reference.' It names the specific resource (custom-order inquiry) and the verb (capture/submit), distinguishing it from the sibling tools that check availability or retrieve menus.
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 when to use the tool (to submit a demo custom-order inquiry) but does not explicitly state when not to use it or mention alternatives like check_custom_order_availability. The demo caveat provides some context but no direct comparison with siblings.
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 the full burden. It clearly indicates a read-only reporting operation by specifying the exact outputs: whether lead time is met, days out, and earliest available date. It does not cover edge cases or validation behavior, but the core behavior is well disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-structured sentence that front-loads the input ('Given a requested YYYY-MM-DD date') and lists the three concrete outputs. Every word earns its place with no fluff.
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 the lack of annotations and output schema, the description explains the main return values but omits parameter semantics for orderType and provides no usage guidance versus sibling tools. It is minimally viable for a simple availability check but has clear gaps.
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 only clarifies the 'date' parameter format (YYYY-MM-DD). The optional 'orderType' parameter is completely undocumented, leaving the agent without guidance on its values, purpose, or effect on the availability check.
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 reports whether a date meets custom-order lead time, how many days out, and the earliest available date. This specific verb+resource distinguishes it from sibling tools like submit_order_inquiry, get_menu, and get_business_profile.
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 gives clear context: use when you have a requested date and need availability/lead-time information. It does not explicitly name alternatives or exclusions, but the purpose is unambiguous, so it narrowly misses a 5.
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 the full burden. It discloses the core behavior (listing and grouping, optional filtering) but does not mention return format, pagination, or behavior for invalid categories. This is adequate for a simple read-only tool but lacks some transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that provides essential information without redundancy. The optional filter is clearly separated by a period, making it easy to parse.
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?
For a tool with one optional parameter and no output schema, the description covers the core functionality adequately. It could mention the structure of the output or behavior when no category is provided, but given the simplicity, it is sufficiently complete.
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?
The schema only defines 'category' as a string with no description (0% coverage), so the description's explanation that it filters to a single category with concrete examples (cakes, pastries, etc.) adds significant meaning 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 uses a specific verb ('List') and resource ('menu items') with a clear grouping behavior ('grouped by category'), and it distinguishes itself from sibling tools focused on orders and business profile.
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 clearly indicates the optional category filter with examples, which implies when to use the tool. It does not explicitly mention alternatives, but sibling tools are clearly unrelated, so no exclusion is necessary.
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 provided, the description relies on 'Return' to signal a read-only operation, but it does not disclose additional behavioral traits such as caching, data freshness, or error handling. It provides basic transparency but leaves room for more.
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?
A single sentence efficiently lists the returned fields with no redundancy. The description is front-loaded with the purpose and enumerates contents compactly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description fully enumerates the return payload (name, tagline, hours, address, phone, pickup/delivery), making it complete for its complexity. There is no missing essential information.
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?
The input schema has zero parameters, and the description naturally does not need to explain parameter behavior. The baseline for zero-parameter tools is 4, and the description meets this without adding unnecessary detail.
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 uses the verb 'Return' with the specific resource 'bakery's core profile' and enumerates the fields, clearly distinguishing it from sibling tools like get_menu or check_custom_order_availability. This is a specific verb+resource with clear scope.
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 the tool is used when the bakery's general profile information is needed, which is clear context for the given zero-parameter tool. However, it does not explicitly state exclusions or alternatives to sibling tools, so it falls short of a 5.
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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