local-mysql
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
The two tools have clearly distinct purposes: 'execute' handles write operations (INSERT/UPDATE only), while 'query' handles read operations (SELECT only). Their descriptions explicitly define non-overlapping scopes with specific allowed statement types, leaving no ambiguity for an agent to misselect between them.
Naming Consistency5/5Both tools follow a consistent, simple verb-based naming pattern ('execute' and 'query') that clearly indicates their action-oriented functions. The naming is uniform without any mixing of conventions, making it predictable and easy to understand at a glance.
Tool Count2/5With only two tools, this server feels severely under-scoped for a MySQL database interface. While the tools cover basic read and limited write operations, the lack of tools for schema management, data definition, or broader CRUD operations (e.g., DELETE, CREATE TABLE) makes it incomplete for typical database workflows, suggesting the count is too low for the domain.
Completeness2/5The tool surface has significant gaps for a MySQL server. It only supports SELECT, INSERT, and UPDATE, missing essential operations like DELETE, DDL (CREATE/ALTER/DROP), and other CRUD lifecycle functions. This will likely cause agent failures when trying to perform common database tasks, as the coverage is severely incomplete for the implied domain.
Average 4.5/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the read-only nature, query type restrictions, row capping at 1000, parameter binding method, schema selection options, and CTE limitations. However, it doesn't mention error handling, performance characteristics, or authentication requirements, leaving some gaps.
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 efficiently structured with four sentences that each add critical information: purpose and restrictions, schema usage, result capping, and parameter/CTE details. There's no wasted text, and the most important constraints (read-only, SELECT-only) are front-loaded.
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 query tool with 3 parameters, 100% schema coverage, and no output schema, the description provides good context about behavioral constraints and usage patterns. It covers the essential 'what happens when invoked' aspects but doesn't describe the return format or error responses, which would be helpful given the lack of output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the input schema already documents all three parameters thoroughly. The description adds some context about the schema parameter ('choose which database to run against') and params array ('Pass parameters via the `params` array using ? placeholders'), but doesn't provide significant additional semantic value beyond what's in the schema descriptions.
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 verb ('Run a read-only SELECT query') and resource ('against the local FO MySQL database'), making the purpose specific and unambiguous. It distinguishes from the sibling tool 'execute' by explicitly stating this is for read-only SELECT queries only, not for other SQL operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Only single SELECT statements are allowed') and when not to use it ('INSERT, UPDATE, DELETE, and DDL are rejected'). It also mentions an alternative approach ('use fully-qualified table names') and specifies version limitations ('CTEs are not supported in v1'), giving comprehensive usage 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?
With no annotations provided, the description carries full burden and does well by disclosing critical behavioral traits: it specifies allowed statement types (INSERT/UPDATE), rejected statement types (DELETE/DDL), return values (affectedRows and insertId), and operational constraints (single statement, local database). It doesn't mention authentication needs, rate limits, or error handling, but covers the essential mutation behavior.
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 perfectly front-loaded with the core purpose in the first sentence, followed by specific constraints and implementation details. Every sentence earns its place by providing essential information about allowed operations, parameter usage, and return values without any redundancy or wasted words.
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 mutation tool with no annotations and no output schema, the description does an excellent job covering purpose, constraints, parameter usage, and return values. It could be more complete by mentioning authentication requirements or error scenarios, but given the complexity and lack of structured fields, it provides substantial contextual information to guide proper tool usage.
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?
Schema description coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema: it explains the relationship between sql and params parameters ('Use ? placeholders and pass values via the `params` array'), clarifies the purpose of the schema parameter ('Use the `schema` parameter or fully-qualified table names'), and provides implementation guidance that helps understand how parameters work together.
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 specific action ('Run a single INSERT or UPDATE statement'), the target resource ('against the local FO MySQL database'), and distinguishes from the sibling tool 'query' by specifying allowed statement types. It provides precise verb+resource+scope differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (for INSERT/UPDATE statements) and when not to use it (DELETE, DDL, and other statement types are rejected). It also provides clear alternatives by mentioning the sibling tool 'query' implicitly through contrast, and gives specific implementation guidance about schema usage and parameter binding.
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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