bt-ops-mcp-server
Server Quality Checklist
Latest release: v0.1.2
- Disambiguation5/5
open_settings and get_settings_status are clearly distinct: one launches/reuses a settings page and returns a URL, while the other reports the status (why not in business mode, config path, next step). No overlap or confusion.
Naming Consistency5/5Both tools follow a verb_noun snake_case pattern (open_settings, get_settings_status), providing a consistent and predictable naming convention.
Tool Count3/5With only two tools, the server feels thin, especially for a settings-related domain. This is borderline but acceptable for a narrowly-focused utility.
Completeness2/5The tool set covers opening settings and checking status but lacks any update, reset, or configuration modification tools. This leaves a significant gap for any agent needing to actually change settings, making the surface incomplete.
Average 4.2/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true and destructiveHint=false, and the description adds that the tool cannot be closed and may reuse an existing settings page. This provides useful behavioral context beyond the structured hints, with no contradiction.
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 front-loads the built-in/cannot-close caveat before stating the action and return value. Every phrase adds relevant information with no redundancy.
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?
The tool is simple, parameterless, and has no output schema. The description explains the action, the return value (access address), and key behavioral constraints. It could be more specific about the address format, but it is adequate for this low-complexity tool.
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 tool has zero parameters and schema description coverage is 100% (empty schema). With no parameters, the baseline is 4, and the description correctly implies no configurable inputs are needed.
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 specific verbs ('启动或复用' = launch or reuse) and a clear resource ('本机设置页' = local settings page), and states it returns an access address. This distinguishes it from the sibling get_settings_status, which is a status check.
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?
No guidance on when to use this tool versus get_settings_status. The note that it is built-in and cannot be closed is a constraint, not usage direction. No alternatives or exclusions are mentioned.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing a safe read-only operation. The description adds context by noting the tool is built-in and cannot be turned off, and specifies the exact information it returns (reasons, configuration path, next steps). This goes beyond basic metadata without contradicting annotations.
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, compact sentence that front-loads the key context (built-in, cannot be disabled) followed by the functional output. Every word adds value—no fluff or repetition—making it highly efficient for an AI agent 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 zero-parameter, read-only status tool with no output schema, the description provides a complete picture: what it does (returns status info), when it applies (restricted mode), and what content it returns (reasons, path, next steps). It doesn't mention return format, but that's not required given the simplicity and the tool's purpose. The sibling tool is not referenced, but the name difference is self-explanatory.
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, so the baseline is 4 as per guidelines. The description adds no parameter-specific details because none are needed. It fully compensates for the absence of parameters by explaining the tool's output focus, which is sufficient.
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 function: it returns reasons for not entering business mode, configuration path, and next steps in restricted mode. It uses a specific verb ('返回' meaning 'returns') and resource ('settings status'), distinguishing it from the sibling tool 'open_settings' which performs a different action (opening settings).
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 specifies the context for use: '受限模式下' (in restricted mode), indicating when this tool is relevant. It does not explicitly mention alternatives or exclusions, but the behavior is clear enough that an agent can infer when to invoke it. The sibling tool's name 'open_settings' contrasts with the status-returning purpose, implicitly guiding selection.
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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