Count occurrences of a character (e.g., how many 'r' in 'strawberry').
| Name | Required | Description | Default |
|---|---|---|---|
| char | Yes | Character to count | |
| text | Yes | The text to search in | |
| case_sensitive | No | Case sensitive counting |
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| count | Yes | ||
| character | Yes | ||
| positions | Yes | ||
| case_sensitive | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the core behavior (count characters) and gives an example, but does not mention side effects, performance, or detailed case-sensitivity handling (though the parameter default is documented in schema). It is adequate for a simple read operation.
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 concise sentence with an embedded example. It is front-loaded with the action and contains no extraneous information. Every word earns its place.
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 tool's simplicity and the presence of an output schema (covering return values), the description is complete. It explains the purpose and usage with an example, leaving no significant gaps for correct invocation.
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%, so baseline is 3. The description adds value by providing an example that illustrates how text and char work together, clarifying the semantics beyond the parameter descriptions alone.
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 states the tool counts occurrences of a single character in a string, with a concrete example (how many 'r' in 'strawberry'). This distinguishes it from sibling tools like count_all_chars (counts all characters), count_substring (counts substrings), and count_digits (counts digits).
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 for counting a specific character but lacks explicit guidance on when to use this tool versus alternatives (e.g., count_substring for multi-character patterns). No exclusions or context for case_sensitive parameter behavior is provided beyond the schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as multiple random generators (random_integer, random_number), duplicate hashing functions (hash_md5, md5_checksum), and near-identical tools (compare, compare_2, compare_decimals). The sheer number of tools and lack of clear boundaries make it difficult for an agent to differentiate.
Naming is highly inconsistent. There are duplicate tools with different names (camel_case vs to_camel_case, slug vs slugify), arbitrary suffixes like '_2', and mixing of patterns (e.g., generate_password vs password_entropy). No clear convention is followed.
With 572 tools, the server is massively overpopulated for any coherent purpose. It includes trivial endpoints (true_endpoint, null, hello_world) and numerous duplicates, far exceeding a well-scoped utility set.
While the server covers many domains (math, strings, dates, colors, etc.), the presence of duplicate and trivial tools indicates a lack of thoughtful curation. There are gaps in basic operations (e.g., no dedicated file or network tools), and many tools are redundant.
