get_trending
Trending/popular AI tools by velocity (stars growth, saves, updates).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Lookback window in days (default 7) | |
| limit | No | Max results (default 10, max 24) |
Trending/popular AI tools by velocity (stars growth, saves, updates).
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Lookback window in days (default 7) | |
| limit | No | Max results (default 10, max 24) |
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, the description bears full burden. It explains sorting criteria but omits details like return format, pagination, or required authentication. It is partially transparent.
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, concise sentence with no superfluous words, achieving maximum efficiency.
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 simple tool with 2 optional parameters and no output schema, the description is adequate but leaves gaps about return structure and edge cases.
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 does not add additional meaning beyond what the schema already provides.
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 returns trending/popular AI tools sorted by velocity (stars growth, saves, updates), distinguishing it from sibling tools like explore or get_tool.
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 usage for getting trending tools but does not explicitly state when to use this tool vs alternatives like explore or compare_tools.
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 clearly distinct purpose: comparing, exploring, getting details, trending, listing, and resolving. No overlap.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., compare_tools, get_tool, list_collections). Even 'explore' is a single verb, fitting the pattern.
7 tools is well-scoped for a tool discovery server, covering browsing, details, comparison, and recommendations without being overwhelming.
Covers most discovery needs (browse, trend, compare, detail) but lacks a general search tool or filtering by features, a minor gap.