Compare two strings with Sorensen-Dice similarity, scoring from 0 for no shared bigrams to 1 for identical. Returns one deterministic value for exact, reproducible text matching.
Sorensen-Dice similarity of two strings, from 0 (no shared character bigrams) to 1 (identical). One deterministic comparison.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | ||
| b | Yes |
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds meaningful value beyond them: the 0-1 output scale and its interpretation (0 = no shared character bigrams, 1 = identical) tell the agent how to read the result, which the annotations do not. Determinism partly restates idempotentHint.
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?
Two tight sentences, front-loaded with the algorithm and resource and followed by the range interpretation. Every clause carries information; nothing is redundant.
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 two-argument pure function with no output schema, the description is nearly sufficient because it defines the return semantics. Minor gaps remain: no note on case sensitivity, unicode/bigram normalization, or empty-string edge cases.
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% and the parameters are bare 'a' and 'b', but the description compensates partially by stating both inputs are strings ('two strings'). It does not state which argument is the reference vs. the candidate, whether order matters, or empty-string behavior, so it only partly fills the gap.
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 names the exact algorithm (Sorensen-Dice), the resource (two strings), and the output scale, so an agent knows precisely what computation it performs. It does not explicitly distinguish itself from the nearest siblings fuzzy_match or diff_text, which is the only thing keeping it from a 5.
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?
Usage is implied rather than stated: 'of two strings' and 'one deterministic comparison' suggest a single pairwise similarity check, but there is no explicit guidance on when to pick this over fuzzy_match or diff_text, nor any exclusions or preconditions. Adequate but leaves the sibling-routing decision to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.