near-contract
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
Tools are mostly distinct: metadata, state, view methods, interface explanation, and transaction decoding each target a different aspect. The slight overlap between get_contract_metadata and explain_contract_interface (both reveal methods) is mitigated by metadata being raw and explain being high-level.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern in snake_case: get_contract_metadata, call_view_method, decode_transaction, get_contract_state, explain_contract_interface. No mixed conventions or ambiguous verbs.
Tool Count5/5Five tools is well-scoped for a contract inspection/analysis server. Each tool serves a clear purpose without redundancy, and the count is within the ideal range for a focused MCP server.
Completeness4/5The tool surface covers the core needs for understanding NEAR contracts: metadata, raw state, view methods, interface explanation, and transaction decoding. A minor gap is the lack of a tool to simulate or estimate gas for view calls, but the current set is coherent and functional.
Average 3.5/5 across 5 of 5 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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavior. It only says 'Analyzes' and 'provides explanation,' but does not disclose whether it is read-only, what data it accesses, potential costs, rate limits, or what form the explanation takes. This is a minimal transparency gap.
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, clear sentence with no wasted words. It front-loads the main verb and outcome, and is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and only 2 parameters, the description should provide more context about what the explanation includes, whether it's a textual summary, and any caveats. The current description leaves the return format and depth of analysis unspecified, so it is incomplete for an agent deciding whether to use it.
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%, so the parameters are already documented in the schema. The description adds no additional meaning beyond the schema, which is acceptable per baseline 3. It does not explain how contract_id or network affect the explanation, but it also does not need to given high schema coverage.
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 uses a specific verb ('Analyzes') with a clear resource ('a contract') and outcome ('human-readable explanation of its purpose and main functions'). This clearly distinguishes it from sibling tools like get_contract_metadata or call_view_method, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states what the tool does but provides no guidance on when to use it versus alternatives. It does not mention when to prefer this over get_contract_metadata or call_view_method, nor any exclusions or preconditions.
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, the description carries the full burden of behavioral disclosure. It indicates the tool is a read operation by 'Fetches' and lists what will be retrieved, but it does not explicitly confirm non-mutating behavior, error conditions, or response structure. This is useful but not richly detailed.
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 focused sentence that efficiently states the tool's purpose and key outputs. There is no redundancy, fluff, or repetition of schema details, making it highly concise and easy to parse.
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 absence of an output schema or annotations, the description gives a reasonable summary of the return contents but lacks contextual guidance on selecting this tool over similar siblings. The moderate complexity of the tool calls for more usage context, so the description is adequate but incomplete.
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 provides full descriptions for both parameters, including the network default, so the description adds no parameter-specific meaning. The summary of output contents (code hash, storage usage, etc.) is contextual rather than parameter-related, so the tool meets the schema-coverage baseline.
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 uses the verb 'Fetches' with a specific resource ('contract metadata') and enumerates concrete examples (code hash, storage usage, detected methods/standards), making the tool's purpose unambiguous. While it doesn't explicitly differentiate from sibling tools like get_contract_state, the metadata focus is distinct enough for basic selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no explicit guidance on when to use this tool versus alternatives such as get_contract_state or explain_contract_interface. No prerequisites, exclusions, or contextual triggers are mentioned, leaving the agent to infer usage solely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. While it states the output includes actions and effects, it does not explicitly confirm the operation is read-only, mention prerequisites, or describe error behavior. This leaves significant transparency gaps for an agent to safely invoke the 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 and front-loaded sentence. It wastes no words, directly stating the verb and resource, and adds a brief scoping clause about actions and effects.
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?
The tool has a clear three-parameter schema but no output schema, so the description must compensate for missing return-value details. It partially does by mentioning actions and effects, but lacks information about output format, error handling, or network-specific behavior. The description is adequate but leaves gaps given the lack of structured output metadata.
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 provides descriptions for all three parameters with 100% coverage, including default and enum values. The description adds no additional parameter semantics, 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 uses specific verbs 'decodes and explains' and a specific resource 'NEAR transaction', clearly distinguishing it from the contract-oriented sibling tools. Mentioning 'all actions and their effects' further clarifies the scope, making the purpose explicit and unambiguous.
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 decoding transactions, which is distinct from the contract-focused siblings, but it does not explicitly state when to use this tool versus alternatives. No exclusions or alternative tool references are provided, so guidance remains only implicit.
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?
No annotations are provided, so the description carries the full burden. It clearly discloses the read-only nature, which is the key behavioral trait. However, it does not describe error behavior, return format, or any side effects (though view methods are non-mutating by definition).
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?
A single, front-loaded sentence with no wasted words. It conveys the core purpose immediately and includes the crucial read-only qualifier.
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?
The tool is simple and the schema covers all parameters, so the description is minimally adequate. However, with no output schema, the description omits what happens after the call (e.g., return value). For a generic view method, the return is unknown, but mentioning that it returns the contract's result would add useful 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%, so the baseline is 3. The description adds 'read-only' and 'any' but these are repetitive of the schema's field descriptions (e.g., 'view method'). It does not materially enrich parameter understanding beyond what the schema already provides.
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?
Description specifies a clear verb ('calls') and resource ('view method on any NEAR smart contract'), and explicitly marks it as read-only. This distinguishes it from sibling tools that handle metadata, state, transactions, or interface explanations.
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: call this when you need to invoke a view method on a NEAR contract. However, it provides no explicit when-not-to-use guidance or comparisons with sibling tools, so usage context is only implied.
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, the description carries the full burden of behavioral disclosure. It discloses that the tool performs a read operation and that results are raw and optionally filtered by key prefix, but it does not mention return format, pagination, authentication, or any side effects. It adds some context but is not comprehensive.
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 words. It is front-loaded and every word contributes meaning, making it efficient and easy to read.
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?
For a simple read tool with good schema coverage, the description is adequate but lacks return value information (no output schema) and does not explain what the raw state entries look like. It also does not specify prerequisites or limitations, leaving a few gaps in 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%, so the schema fully documents each parameter. The description adds minimal value by mentioning the optional key prefix filter, but this information is already present in the schema. It does not clarify network or contract_id beyond what the schema provides.
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 a specific action ('Reads raw contract state entries') and resource ('contract state entries'), and the optional key prefix filter adds specificity. It distinguishes itself from siblings like get_contract_metadata and call_view_method by focusing on raw state access.
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 retrieving raw state entries but provides no explicit guidance on when to choose this tool over alternatives, nor does it mention exclusions. It sets context but lacks direct 'when to use' instructions.
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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