Toolport
Server Quality Checklist
Latest release: v1.15.0
- Disambiguation5/5
Each tool has a distinct, non-overlapping purpose: searching for tools, calling a tool, fetching truncated results, and reporting status. There is zero ambiguity in their roles.
Naming Consistency5/5All tool names follow the consistent pattern `toolport_verb_noun` (call_tool, fetch_result, search_tools, status) using snake_case, making them predictable and easy to understand.
Tool Count5/5Four tools is exactly right for a meta-server acting as a gateway: discovery, invocation, pagination handling, and status reporting. No tool feels excessive or missing.
Completeness5/5The tool set covers the full lifecycle of working with external tools: search to discover, call to invoke, fetch to page through large results, and status to monitor. There are no apparent gaps for its stated purpose.
Average 4.4/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 7 of 10 community issues answered or closed in the last 6 months
- 1087 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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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 bears the full burden. It indicates a non-destructive read operation, but does not disclose any potential side effects, caching, rate limits, or performance characteristics. For a simple report tool, this is minimally adequate.
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 sentence that front-loads the core purpose and efficiently enumerates the report contents with no wasted words.
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?
Given the tool's simplicity (no parameters, no output schema), the description fully covers what the tool does and returns. It is complete for the context.
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 tool has zero parameters and the input schema is fully documented (100% schema description coverage). The description adds no parameter details, but none are needed. Baseline 4 for 0-parameter tools applies.
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 reports Toolport's status, listing specific data points (MCP servers, tool counts, token/dollar savings). This distinguishes it from sibling tools (search, call, fetch) 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining status information, but it does not explicitly state when to use it versus alternatives or provide any exclusion criteria. It lacks clear usage guidance beyond the implicit context.
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, the description carries the full burden. It discloses that the tool paginates through a truncated result, that nothing is lost, and how the marker works. Could mention behavior for invalid cursors, but overall transparent.
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?
Three sentences, front-loaded with purpose, then usage, then reassurance. No unnecessary words. Efficient and well-structured.
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 no output schema, the description doesn't detail return format but implies it returns the next chunk. It covers the trigger and parameters adequately. Could specify what to expect on success or failure, but mostly complete.
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% for both parameters, with descriptions already defining cursor and offset. The description adds context that the offset is shown in the marker, but this is minor. Baseline 3 is appropriate as the description adds marginal value over the 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 clearly states the tool reads more of a large tool result that was truncated, using a cursor and offset. It distinguishes itself from sibling tools like toolport_call_tool (calls a tool) and toolport_search_tools (searches tools).
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 explicitly explains when to use: when a result is too big and a marker is returned. It details the parameters (cursor and offset from the marker) and reassures that nothing was lost. No explicit exclusion of alternatives, but the context makes it clear.
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 provided, so description carries full burden. It describes invocation but doesn't clarify side effects (read-only vs write), return value, or error behavior. Adequate but lacks depth for a call 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?
Three sentences, no fluff, purpose first, then structural detail, then caution. Efficient and front-loaded.
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 simple parameters and no output schema, the description covers usage and pitfalls. However, it omits return value (implied by sibling tools) could be slightly more explicit.
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 covers 100% of parameters, but description adds value by explaining the nesting of arguments and giving context about not inventing identifiers, which helps agent avoid common mistakes.
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 it invokes a tool discovered via toolport_search_tools, with specific verb 'Invoke' and resource 'tool'. It distinguishes from sibling tools (toolport_search_tools, toolport_fetch_result, toolport_status) by its unique action.
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 says when to use (after searching), how to structure arguments (inside `arguments` object), and what not to do (never invent identifiers). Provides fallback guidance to call list/get tools if needed.
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 provided, so description carries full burden. Discloses that large input schemas may be omitted (schemaOmitted) and suggests searching exact name for full schema. Also notes that many servers expose generic API bridges. Does not mention any side effects or auth needs, which is acceptable for a read-only 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?
Description is lengthy but every sentence provides valuable guidance. It front-loads the main purpose and then offers detailed strategies. Could be slightly more concise, but efficient given the complexity.
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?
Given the tool's role (search across multiple servers) and lack of output schema, the description is remarkably complete. Covers scoping, handling incomplete results, schema omission, and integration with sibling tools. Leaves no major gaps for an AI agent to misuse.
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?
Schema coverage is 100% but description adds extra: explains empty query with server to list all tools, gives usage examples ('list emails'), and clarifies limit range (default 25, up to 200). Adds value beyond 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 it is the gateway to all MCP servers' tools, using verbs like 'search' and 'list'. It distinguishes itself from siblings (toolport_call_tool, toolport_status) by specifying its role as the discovery entry point.
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?
Provides explicit directives: use this FIRST for any external action, do not assume capability missing until searched, once matched call it without further searching. Gives strategies like using server scope, empty query, or raising limit. Mentions sibling toolport_status for listing servers.
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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