string_replace

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that ALL occurrences are replaced (not just the first), which is genuine behavioral information, but it omits case-sensitivity, literal-vs-regex matching, and empty-input behavior.

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, front-loaded sentence with zero filler that communicates the operation and its scope precisely.

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?

An output schema exists, so return values need not be explained. For a simple pure string utility the description is nearly sufficient, with only edge-case behavior (case sensitivity, regex interpretation) left unstated.

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 maps its wording onto all three parameters (old = substring to find, new = replacement, text = source), which gives basic semantics, but adds no detail on empty strings, overlapping matches, or whether matching is literal.

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?

States a specific verb (replace) and resource (string) with the exact substitution model: 'all occurrences of old with new'. This clearly separates it from no-op siblings like string_reverse or string_uppercase, though it does not name an alternative tool explicitly.

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 when-to-use or when-not-to-use guidance, no mention of prereconditions, and no routing to any sibling. The agent must infer usage purely from the verb.

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