string_char_count

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

With no annotations, the description carries the full behavioral burden, yet it omits meaningful traits: whether matching is case-sensitive, how an empty char is handled, or whether the search is literal or pattern-based. For a counting utility these ambiguities directly affect correctness, so the disclosure is thin.

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 tight sentence with the verb and both implied inputs front-loaded; nothing is wasted or padded.

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-value explanation is unnecessary. However, for a two-required-parameter tool with 0% schema coverage and no annotations, the description leaves the case-sensitivity and edge-case behavior unresolved, which is the main gap an agent would hit.

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 bare 'char' and 'text' parameters get no documentation. The description implicitly maps to both (a character and a string) and clarifies that char is a single character, but adds no detail on case handling or validation.

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 verb (count) and resource (occurrences of a character in a string), which is clear on its own and reasonably distinguishable from siblings like string_length (counts all characters). It does not explicitly contrast itself with string_length, so it stops short of 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?

There is no guidance on when to use this versus string_length, string_replace, or matches_regex. No preconditions, no exclusions, no alternatives named; the agent must infer the use case entirely.

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