string_lcs

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden, but this is a stateless pure computation so the risk profile is inherently low. It does disclose that a similarity score is returned, adding one piece of behavioral information. It does not state that the operation is side-effect free, deterministic, or how the score is normalized (length ratio, absolute count, etc.).

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?

A single efficient sentence with the core verb front-loaded and zero filler. It is appropriately sized, though the 'similarity score' clause could be folded into an output description rather than left dangling.

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?

With no output schema, the description should say more about the return value; it only alludes to a 'similarity score' without stating scale or the shape of the result (subsequence string plus score). For a simple two-parameter pure function this is adequate but leaves gaps an agent must guess at.

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 100%, with both 'a' and 'b' documented in the schema, so the baseline is 3. The description adds nothing beyond the schema – it does not clarify ordering effects, case sensitivity, or whether the two arguments are symmetric.

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?

Names a specific verb and resource ('Find the longest common subsequence of two strings'), so the operation is unambiguous. It also signals an additional output ('similarity score'). It does not name or contrast with nearby siblings like longest_common_prefix or edit_distance, so differentiation is left to the reader.

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?

There is no guidance on when to prefer this over string_distance, edit_distance, hamming_distance, jaccard_similarity, or the other string-comparison siblings. No conditions, no exclusions, no alternatives are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.