vremly
OfficialServer Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct role: search finds endpoints, describe gives full schema details, and request executes the call. There is no overlap or ambiguity between them.
Naming Consistency4/5All tools share the vremly_ prefix and use snake_case, making the set predictable. The only minor inconsistency is that vremly_request omits the 'endpoint' object present in the other two names.
Tool Count5/5Three tools is an elegant fit for an API gateway covering 1,037 operations. Each tool earns its place in a clear discovery-to-execution pipeline without redundancy.
Completeness5/5The workflow is complete: search to find endpoints, describe to understand the required shape, and request to execute. There are no obvious dead ends or missing operations for the stated purpose of interacting with the Vremly API.
Average 4.5/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and does well by explaining authentication, organization scoping, and that key scopes determine write permissions. It stops short of detailing error behavior or specific side-effect warnings, but the contingent write capability is disclosed.
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 concise and front-loaded, with the core purpose in the first sentence followed by relevant authentication and usage notes. No redundant or filler content.
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 gives enough context for an agent to use the tool: what it does, how authentication works, and what to substitute. It does not specify response formats beyond status/body, but for a generic request tool this is reasonably complete.
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 the baseline is high. The description adds useful context by emphasizing path placeholder substitution and confirming that body/query are optional, which goes slightly beyond the schema descriptions.
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: calling a Vremly API endpoint and returning its status and body. This verb-focused purpose distinguishes it from sibling tools that search or describe endpoints.
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?
Provides some practical guidance, such as substituting real IDs and not sending placeholders, but does not explicitly mention when to prefer this tool over the sibling search/describe tools.
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 discloses a critical, non-obvious server behavior (silent stripping of unknown fields) and mentions that a credential is accepted, though it doesn't detail authentication requirements. It does not contradict any annotations (none exist). The description goes beyond a simple definition by explaining the consequence of misuse.
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 sentences with zero waste. The primary purpose is front-loaded, followed by a high-value usage warning. Every word earns its place; there is no redundancy.
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?
There is no output schema, so the description must explain what is returned. It explicitly lists the components (path/query parameters, request body schema with required fields, response schemas, and credential). It also covers when to use it relative to siblings. Given the tool's moderate complexity (2 parameters, no nested objects), the description is complete enough for an agent to call it correctly.
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 both parameters ('path' and 'method') are already documented with formats and examples. The description adds no additional semantic detail beyond what the schema provides, so a baseline of 3 is appropriate. It does reinforce that the path must be a template as returned by search, but that is already in the schema description.
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 clear verb ('Describe') with a specific resource ('one Vremly endpoint') and enumerates the exact content (parameters, body schema, responses, credential). It distinguishes itself from siblings: it is not a search tool (vremly_search_endpoints) nor a request tool (vremly_request).
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?
Explicitly instructs when to call this tool ('Call this before vremly_request') and explains why (server validation strips unknown fields silently, so a misspelled key fails invisibly). This provides both a positive trigger and a warning that motivates its use, without needing to infer.
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?
The description implies a read-only search operation without stating it explicitly. Since no annotations are provided, the description carries the full burden of disclosing side effects. While the nature of a search tool makes mutations unlikely, explicitly noting that it does not modify any resources would improve transparency.
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 concise and well-structured. It opens with the primary action and resource, then provides scope, use-case guidance, and output details in a logical flow. Every sentence serves a purpose, with no fluff or unnecessary repetition.
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?
The description is complete for a search tool. It explains what the tool does, when to use it, what it returns, and how to get more detail via the sibling describe_endpoint. It does not need to explain output schema since it explicitly mentions the returned fields. This covers all essential context an agent needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all three parameters (query, limit, method) with 100% description coverage. The description adds valuable nuances: the 'query' parameter's requirement that all terms must match, and the 'method' parameter being an optional filter. This enhances the schema without redundancy.
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 purpose: searching the Vremly API by keyword. It specifies the scope (1037 operations covering various domains) and the primary use case (when the exact path is unknown). This unambiguously distinguishes it from the sibling describe_endpoint and request tools.
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 instructs to 'start here' when the path is unknown, and it outlines what the tool returns (method, path, summary, tags) and how to proceed for full details (pass result to describe_endpoint). This gives clear guidance on when and how to use it, including a natural handoff to the next tool.
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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