Independently score each candidate's relevance to your query, then sort them; original order breaks ties.
Independently score relevance of each supplied candidate, then sort; candidate order breaks ties.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| top_k | No | ||
| candidates | Yes |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a behavioral nuance beyond annotations: scoring is independent per candidate, and tie-breaking uses original candidate order. This adds value beyond the readOnly and idempotent hints. However, it does not mention output format or any side effects (e.g., whether scores are returned), which could be useful but is not critical given the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately states the core action and a key behavioral rule. Every word earns its place; there is no filler or redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three parameters, no output schema, and zero parameter descriptions, the description leaves out essential context. It does not explain the return value (sorted list? scores? both?), the meaning or effect of top_k, or any constraints on candidate structure beyond what the schema shows. An agent cannot fully predict the tool's behavior from this description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It implies the roles of query and candidates through 'score relevance' and 'each supplied candidate,' but it does not explicitly explain them, nor does it mention the optional top_k parameter at all. The agent gets no information about what top_k controls or how to use it, making parameter semantics incomplete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action: independently score each candidate's relevance, then sort, with tie-breaking by original order. This clearly distinguishes it from sibling tools like system_one_compare (comparison) or system_one_extract (extraction), giving an agent an unambiguous sense of what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. It only states what the tool does, leaving the agent to infer the appropriate context from the name alone. There is no explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.