bocha-ai-search
Server Quality Checklist
Latest release: v0.0.1
- Disambiguation5/5
Only one tool exists, so there is no ambiguity in tool selection. The single tool's purpose is clear.
Naming Consistency5/5The tool name 'bocha_web_search' follows a consistent snake_case convention and clearly communicates its functionality, making it predictable.
Tool Count3/5A single tool is borderline for a search server; it feels thin compared to typical search services that might offer multiple search types or additional utilities, but it is not excessive.
Completeness5/5The web search tool fully covers the core search operation, including detailed result information and flexible output formats, with no obvious gaps in the provided domain.
Average 3.6/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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
- Behavior3/5
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 the output content and available formats (Markdown vs raw JSON), which adds behavioral context. However, it omits details like rate limits, result ordering, error behavior, or authentication requirements, leaving notable gaps.
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 a single sentence that front-loads the core purpose and then lists useful output details. It is succinct and avoids fluff, though it could be split into two sentences for better readability. Still efficient for the information conveyed.
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?
With no output schema and no annotations, the description must explain what the tool returns; it does enumerate result fields and output formats. However, it lacks information about result ordering, pagination, error handling, or any prerequisites, leaving the tool 'usable but not fully specified' for complex decisions.
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 covers all five parameters with descriptions (100% coverage). The description adds no extra meaning beyond the schema, merely referencing the output format options already documented. Baseline 3 is appropriate given the schema's completeness.
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 performs web search using Bocha AI and specifies the exact result fields (title, URL, snippet, site name, icon, publish time). It uses a specific verb+resource combination, making the tool's function unmistakable even without sibling differentiation.
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 usage for web search needs but provides no explicit guidance on when to use this tool over alternatives or when not to use it. Since no alternatives are mentioned, the context is clear enough for a basic search tool, but exclusions and prerequisites are absent.
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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