Compare decimal numbers with detailed explanation (handles 0.9 vs 0.11 correctly).
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First decimal number as string | |
| b | Yes | Second decimal number as string |
| Name | Required | Description | Default |
|---|---|---|---|
| a | No | ||
| b | No | ||
| code | No | ||
| error | No | ||
| symbol | No | ||
| a_as_float | No | ||
| b_as_float | No | ||
| comparison | No | ||
| difference | No | ||
| description | No | ||
| explanation | No | ||
| larger_number | No |
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, and the description only mentions 'detailed explanation' without disclosing side effects, error handling, or exact return format. More behavioral context is needed.
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, front-loaded sentence that efficiently conveys the core value and key differentiator with no wasted words.
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 that an output schema exists, the description adequately explains what the tool does, but lacks details on prerequisites or limitations, making it minimally viable for a straightforward comparison 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 descriptions already clarify parameters, but the description adds the crucial context that string inputs are used to avoid precision issues, adding value beyond the schema.
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 compares decimal numbers and emphasizes its ability to handle cases like 0.9 vs 0.11 correctly, distinguishing it from other comparison tools.
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 use for decimal number comparison to avoid floating-point errors, but does not explicitly state when to use or not use this tool versus siblings like 'compare' or 'compare_2'.
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.
