Order a technical summary (600-1,000 words, same-day delivery). Pay $19 USDC on Ethereum mainnet.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Email address to receive the summary | ||
| topic | Yes | Topic or document to summarize |
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 provided, so the description carries full burden. It discloses that this involves a payment of $19 USDC on Ethereum mainnet and same-day delivery. However, it does not mention prerequisites, side effects (e.g., wallet connection), or what occurs on failure.
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 that efficiently conveys the product, specifications, cost, and payment method with zero 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?
While the description covers key aspects (product, length, delivery, price), it does not explain what the agent receives (e.g., confirmation, email delivery) or any steps required from the user. With no output schema, this gap reduces completeness. Sibling context helps but not fully.
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 clear descriptions for both parameters. The description adds no additional meaning beyond the schema, focusing instead on the service output. Baseline 3 is appropriate.
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 verb 'Order' and resource 'technical summary', specifies word count range (600-1,000) and delivery speed (same-day). It distinguishes from siblings by specifying 'technical' vs. blog post, competitor analysis, or market research.
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 clear context that this tool is for ordering technical summaries, with specific constraints (word count, delivery, payment). It does not explicitly exclude alternatives, but the noun 'technical' and sibling names imply when to use.
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.
Each tool has a distinctly different deliverable (blog post, competitor analysis, market research, technical summary), making it easy for an agent to select the appropriate one.
All tool names follow a consistent 'order_<noun>' pattern, which is predictable and clear.
With 4 tools, the server is well-scoped for its purpose of ordering research reports; not too few or too many.
Covers common report types (blog, competitor, market, technical) but lacks options for custom requests or status tracking, though these are minor gaps for the intended scope.