WORKFLOW: weekly competitor movements + actions, with sources. input=competitors. B2B: strategy teams stay ahead. [x402: 25.0 USDC on Base, pay-per-use]
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | service input |
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 discloses the tool is a 'WORKFLOW' and pay-per-use, and mentions output with sources, but it fails to state side effects, authentication needs, output format, or whether the operation is read-only. For a tool with no annotations, this is a significant gap.
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 short and front-loaded with the core workflow: 'weekly competitor movements + actions, with sources.' The B2B context and pricing note are relevant, though the 'WORKFLOW:' prefix and compressed 'input=competitors' phrasing read as jargon and could be clearer.
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?
For a tool with one generic string parameter, no annotations, and no output schema, the description leaves essential questions unanswered: how to format competitor input, what the report/output looks like, when this is preferred over sibling tools, and what the workflow steps are. It is not complete enough for an agent to invoke confidently without further clarification.
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?
The input schema only has a generic 'service input' description, so the description's 'input=competitors' adds meaningful semantic guidance about what to pass. Still, it does not explain format, structure, or examples, so it is helpful but not fully specific.
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 identifies a specific resource ('competitor') and action ('weekly competitor movements + actions, with sources'), and it states the intended audience ('B2B: strategy teams stay ahead'). However, it does not differentiate this tool from sibling tools like competitor-scan or competitive-analysis, so it stops short of full clarity.
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 cases: weekly competitor monitoring with sources, useful for B2B strategy teams. It does not explicitly state when to use this tool over alternatives, nor does it provide exclusions or conditions, so guidance is only implied rather than precise.
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.
The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.
Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.
160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.
The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.