Free. Run any tool not in tools/list (see tool_catalog). Same pricing as a direct call.
| Name | Required | Description | Default |
|---|---|---|---|
| args | No | Args per that tool's inputSchema. | |
| name | Yes | Tool name (see tool_catalog). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / args / descriptionAdded value: +"Args per that tool's inputSchema."Input schema / properties / name / descriptionAdded value: +"Tool name (see tool_catalog)."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare openWorldHint and destructiveHint, so the safety profile is known. The description adds pricing information ('Free', 'Same pricing as a direct call') but does not elaborate on potential side effects or auth requirements beyond what annotations imply.
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?
Two short sentences, front-loaded with the core purpose. Every word earns its place, no redundancy or fluff.
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 dynamic nature of the tool, the description is minimal but paired with schema and annotations it covers the essentials. It could mention error handling or how to discover available tools, but the reference to tool_catalog partially addresses that.
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 coverage is 100% with descriptions for both 'name' and 'args'. The description adds the reference to tool_catalog for name resolution and clarifies that args follow the target tool's input schema, providing marginal value over 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 it runs any tool not in the standard tools/list, referencing the tool_catalog for names. It distinguishes itself from the specific sibling tools by serving as a generic dispatcher, though the term 'tools/list' could be more explicit.
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 provides usage context: use this for tools not in the standard list, and consult tool_catalog for valid names. It does not explicitly exclude scenarios, but the instruction 'see tool_catalog' and the contrast with siblings implies when to use it.
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.
Several tools overlap in fetching and processing web content (fetch_extract, fetch_html, fetch_metadata, html_to_markdown), which could confuse an agent. However, descriptions clarify output types, so most tools are distinguishable.
Names follow mixed conventions: verb_noun (fetch_html, remove_background), noun_verb (csv_query, rss_parse), and noun_noun (tool_catalog, screenshot_url). Each name is descriptive, but the lack of a consistent pattern makes it harder to guess tool names.
With 17 tools, the count is slightly above the ideal 3-15 range but still manageable. The inclusion of 5 meta-tools (pricing, tool_catalog, task_recipes, memory_snippet, use_tool) inflates the count but serves a discovery purpose.
The toolkit covers a broad range of web and data tasks (fetch, parse, query, convert, image, SEO). Minor gaps exist (e.g., no OCR, no image editing), but use_tool can dynamically access additional tools, mitigating incompleteness.