merch-store-mcp
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct concern: store_status checks connection/bridge health, store_open handles navigation, and store_read_log inspects the execution log. There is no overlap in purpose or ambiguous boundaries between them.
Naming Consistency4/5All tools share the store_ prefix and use snake_case, creating a predictable pattern. Minor variation exists between noun-style (store_status) and verb-style (store_open, store_read_log), but the convention is uniform enough for an agent to infer behavior.
Tool Count4/5Three tools is on the lower end but well-scoped for a lightweight bridge/debugging server. Each tool serves a clear and necessary role, and the count aligns with the server's narrow purpose.
Completeness4/5The server covers the core diagnostic workflow: check connection, navigate if needed, and verify via logs. It lacks direct control or configuration tools, but those appear intentionally delegated to the page's own tools, so no significant gaps for its intended use.
Average 4.4/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 provided, the description carries the burden of describing the effect. 'Navigate the connected page' clearly communicates that this tool changes current page state or location. It also adds caveat about typical usage, which is useful behavioral context, though it does not detail error cases or side effects beyond navigation.
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?
Two sentences, front-loaded with the core action and examples, and a clear alternative in the second sentence. No wasted words and the guidance is easy to parse.
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?
This is a simple one-parameter tool with full schema coverage and no output schema requirements. The description covers what it does, gives path examples, and flags when it should be avoided, making it complete for the agent's needs.
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?
The input schema already documents the only parameter 'path' with 'Path beginning with /', so schema coverage is 100%. The description adds examples, which are helpful, but it does not add substantial semantic meaning beyond the schema.
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 action: navigating the connected page to a store path, with concrete examples like '/checkout'. It is specific about the verb and resource, but it does not directly differentiate itself from the sibling tools store_status and store_read_log, instead distinguishing from a different page-level navigate_to tool.
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?
It explicitly tells the agent when not to use the tool ('Most journeys do not need this') and names the preferred alternative ('the page's own navigate_to tool is usually the right one'). This gives clear routing guidance with little ambiguity.
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 takes on the transparency burden. It adds meaningful behavior beyond the name by calling the log 'live' and noting it mirrors the console panel entries, which signals freshness and fidelity. It does not enumerate return structure, but that is reasonably inferred from the 'same entries' phrasing.
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?
Two sentences deliver a definition, a behavioral anchor, and a use-case recommendation with no filler. The core purpose is front-loaded and every phrase earns its place.
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 description is sufficient for a zero-parameter read-only tool: it identifies what is returned, the freshness of the data, and the intended workflow. The only minor gap is the absence of explicit return-format details, but the console-panel reference covers this adequately.
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, so the baseline is 4 under the rubric. The description correctly avoids inventing parameter details and instead focuses on what the log contains and when it should be consulted.
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 opens with a specific verb and resource: 'Read the store's live tool-call log.' It further clarifies the object by referencing the same entries shown in the console panel, which distinguishes it from sibling tools like store_status and store_open.
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 explicitly states when to use the tool: 'Use it to confirm what the store actually did before reporting success.' It provides clear context for invocation, though it does not name alternatives or exclusion conditions.
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 the full burden. It frames the tool as a read-only 'Check' and lists the diagnostic information it surfaces, implying side-effect-free behavior. It stops short of explicitly stating that no state changes or permissions are involved.
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?
Two dense sentences with no filler. The first sentence lists exact checks, and the second gives a clear usage directive. Every word earns its place.
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 status tool with no output schema, the description adequately covers what it reports and when to call it. The only minor gap is that it does not describe the format or shape of the returned status result, but this is not essential for correct invocation.
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, so there is no parameter semantics for the description to add. Per the rubric, a zero-parameter tool receives a baseline of 4.
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 names a concrete diagnostic action ('Check the bridge') and enumerates the specific facts it reports: which page is connected, whether native WebMCP is live, and which store tools are registered. This clearly distinguishes it from siblings like store_open and store_read_log.
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?
It gives an explicit trigger condition: 'Call this first if anything looks wrong.' This tells the agent when to use the tool as a triage step, though it does not explicitly discuss when not to use it or name alternative tools.
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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- Evaluate tool definition quality.
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