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

With no annotations, the description must carry the full behavioral burden. It discloses data sources (Rosetta Code, NIST DADS, cp-algorithms, Skiena) and licensing (CC BY-SA 4.0, educational label), which is useful context, but it omits whether the operation is read-only, how errors (e.g., unknown algorithm) are handled, or any output format details.

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 sentence that front-loads the core purpose and then layers conditional details. It is dense but contains no redundant or filler words, though splitting it into two sentences could improve readability.

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?

Given the absence of an output schema, the description sufficiently explains what is returned: languages, source code, reference links, and licensing. Missing details about error cases or result formatting are minor for a straightforward lookup tool.

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 coverage is 100% for both parameters, setting a baseline of 3. The description adds value by explaining the conditional behavior: without language it lists available languages, and with language it returns the corresponding source code, going beyond the schema's brief parameter notes.

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 clearly identifies the tool's content: implementations of a named algorithm, including languages from Rosetta Code and source code plus reference links when a language is given. It lacks a direct verb like 'retrieve' or 'list', but the resource is unambiguous and no sibling tool overlaps with this functionality.

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 implies usage through the conditional 'with language set, the source code …', but it never states when to use this tool versus alternatives or what prerequisites exist. Usage is inferable for a simple lookup, placing it at the minimum viable level.

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