Get descriptive statistics for a dataset.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
| Name | Required | Description | Default |
|---|---|---|---|
| q1 | Yes | ||
| q3 | Yes | ||
| iqr | Yes | ||
| max | Yes | ||
| min | Yes | ||
| sum | Yes | ||
| mean | Yes | ||
| count | Yes | ||
| range | Yes | ||
| median | Yes | ||
| std_dev | Yes | ||
| variance | 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention the output format, any side effects, or the range of statistics computed. The existence of an output schema is not visible in the description, leaving the agent uncertain about the return value.
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 with no extraneous words. It is appropriately concise, though it could benefit from slightly more detail without becoming verbose.
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 (one parameter) and the presence of an output schema, the description is incomplete as it does not explain what 'descriptive statistics' entails. The agent lacks information about the nature of the results.
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% for the single parameter 'numbers', which is described as 'Comma-separated numbers'. The tool description adds no additional meaning beyond this schema, so it meets the baseline but does not enhance clarity.
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 'Get descriptive statistics for a dataset', which is more specific than just the name 'describe_data'. However, it does not specify which statistics are computed, and it doesn't distinguish clearly from sibling tools like 'average', 'median', etc.
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 tool versus alternatives such as specific statistical measures (e.g., average, median, standard deviation). The description lacks explicit context or exclusions.
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.
