tbro-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
The two tools have clearly distinct purposes: one fetches a specific URL as plain text, the other performs a web search. No overlap in functionality.
Naming Consistency5/5Both tools follow the 'web_' prefix naming convention, making it easy to identify them as web-related. Consistent pattern.
Tool Count4/5With only 2 tools, the set is minimal but appropriate for a focused utility that provides web fetching and search. Slightly small but not insufficient.
Completeness5/5The set covers the two primary web interaction needs: fetching a specific URL and searching the web. No obvious gaps for the stated purpose of plain-text web content.
Average 4.3/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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
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 full burden. It discloses the engine (Mojeek), output format (plain text, no HTML), and benefits (no captcha, no JS, no ads, token savings). It does not mention rate limits or caching behavior, but the disclosed traits are sufficient for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main action and key features. It is efficient and avoids redundancy, though it could be slightly more compact without losing information.
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?
Given the tool has 2 parameters, no output schema, and a sibling tool, the description covers most relevant aspects: engine, output format, token efficiency, and usage scenarios. It lacks detail on the exact structure of results but is generally complete for a search tool.
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?
Schema coverage is 100% with descriptions for both parameters. The tool description adds no extra meaning beyond the schema's parameter descriptions, so the baseline score of 3 is appropriate.
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 it performs web search with flat text output via glyph browser using Mojeek engine. However, it does not explicitly differentiate from its sibling 'web_fetch', which may have overlapping functionality. The purpose is specific but sibling distinction is not provided.
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 (general/text/documentation queries) and when not to (real-time, JS-rendered, paid results), and suggests an alternative (built-in web search). This provides clear usage guidance.
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 carries the full burden. It discloses that the tool strips HTML/JS/navigation/ads and returns flat text, and notes limitations for dynamic pages. However, it omits details like redirect handling, timeout, or whether it follows robots.txt, which could affect 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 a single, well-structured paragraph that front-loads the main action and limitations. Every sentence adds value, with no wasted words. It is appropriately sized.
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?
Given the tool has two parameters, no output schema, and no nested objects, the description explains what it returns (flat text) and its limitations. It is mostly complete but could mention response format or error handling for full context.
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?
Schema description coverage is 100%—both parameters have descriptions in the schema. The tool description adds minimal value beyond restating the default max_chars (8000) and that url must be absolute http(s). No additional semantic enrichment.
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 loads URLs as pure flat text, specifies the resource (web pages), and distinguishes it from inappropriate uses (JS-heavy SPA). It explicitly mentions the verb and resource, providing high clarity.
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 advises when to use this tool (static/text pages) and when not to (JS-heavy SPA), even suggesting an alternative ('built-in web fetch'). This provides clear usage guidance beyond general context.
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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