ohos-mcp-unofficial
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: searching, reading, and listing documentation topics. There is no overlap or ambiguity between them.
Naming Consistency5/5All three tools follow the consistent verb_noun pattern with underscores: find_docs, read_doc, list_doc_topics. The naming is uniform and predictable.
Tool Count5/5Three tools is well-scoped for a documentation lookup server. Each tool addresses a necessary step in the workflow without unnecessary bloat.
Completeness5/5The tool set covers the full documentation workflow: discover topics, search for specific docs, and read full content. No critical operations are missing for the stated purpose.
Average 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
- 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
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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?
With no annotations, the description must carry behavioral disclosure. It says 'Read' and 'full content', which conveys read-only behavior and non-truncation, but does not mention error handling, authentication, or any side effects. This is adequate but minimal for a simple read tool.
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 concise sentence with no redundant or filler words. It front-loads the action ('Read the full content') and adds a clear purpose, making it easy 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 one-parameter, no-output-schema tool with no annotations, the description provides sufficient context to understand what the tool returns and why it exists. It could mention error behavior, but the combination of description and schema is largely complete for a simple read operation.
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 schema provides 100% coverage of the only parameter (objectId) and already notes it is obtained from find_docs. The description adds no additional parameter context beyond the broader purpose, 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads the full content of a specific documentation file, with a specific purpose (code examples and detailed API usage). This distinguishes it from siblings like find_docs (search) and list_doc_topics (topics) by focusing on retrieving the full content for a known document.
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 when detailed examples are needed, but does not explicitly name alternatives or exclusion criteria. The schema notes the ID comes from find_docs, but that is in the schema rather than the description. Thus, usage context is present but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral disclosure burden. It implies a read-only operation ('List all') but does not explicitly mention safety, missing output details, or any restrictions. For a simple list tool, this is minimal but not misleading.
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 concise sentence that front-loads the action and then provides the purpose. Every word earns its place, and there is no redundant or vague phrasing.
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 tool with no output schema, the description covers the essential information: what is listed (documentation categories) and why (to understand the SDK structure). It could explicitly mention the return format, but 'List all...' sufficiently implies a list of categories.
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 is empty, so the baseline for parameter semantics is 4. The description adds context by clarifying the purpose and scope (categories of the HarmonyOS SDK), which goes beyond the empty schema.
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 states a specific action ('List all available documentation categories') and identifies the resource (HarmonyOS SDK). It clearly distinguishes from sibling tools like find_docs and read_doc by focusing on the structural overview.
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 the tool is used to understand the SDK structure but does not explicitly contrast it with sibling tools or state when not to use it. No exclusions or alternatives are mentioned, leaving the decision to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits itself. 'Search' implies a read-only operation, but the description does not explicitly state it is non-mutating or describe the return format (e.g., list of document IDs, snippets). This leaves some uncertainty about what the tool actually does beyond searching, earning a middle score.
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 two concise sentences, front-loaded with the primary action and purpose, followed by usage context. Every word adds value, with no redundancy or filler. It is well-structured and easy to scan.
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?
Given the tool's simplicity (2 params, no output schema), the description covers the core purpose but does not mention what the search returns (e.g., document titles, links, or snippets). Without an output schema, this omission leaves a notable gap in completeness, but the tool is simple enough that the description is acceptable.
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 coverage is 100%, so both parameters are documented. The description adds value by giving concrete examples of query types (UI components, APIs, architectural guidance), which helps users formulate effective queries beyond the schema's generic description. This extra guidance raises the score above the baseline.
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 as searching HarmonyOS/OpenHarmony documentation, with specifics on what can be found (UI components, APIs, architectural guidance). This distinguishes it from sibling tools like read_doc (reading a specific doc) and list_doc_topics (listing topics), making the purpose unambiguous.
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 indicates when to use the tool ('Use this to find UI components, APIs, or architectural guidance'), providing clear context for search-related tasks. It does not explicitly state when not to use it or mention alternatives, but the context is sufficient for basic selection among siblings.
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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