Recommend open source projects for a concrete agent use case and constraints.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| use_case | Yes | ||
| require_d1 | No | Fail closed unless the tool result is backed by D1 instead of seed fallback. | |
| constraints | No |
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?
Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description does not need to cover basic safety. However, it adds no context about how recommendations are generated, what response to expect, or whether results are deterministic. The description is consistent with annotations, so no contradiction.
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 that leads with the action and avoids filler. It is easily scannable and efficient, though its brevity contributes to the lack of detail.
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?
The description is inadequate for a tool with a nested constraints object, no output schema, and multiple parameters. It does not explain what recommendations look like, how constraints are applied, or the role of limit and require_d1. This leaves the agent with significant uncertainty about how to invoke the tool and interpret 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 only 25% (only require_d1 has a description), and the tool description does not compensate. It mentions 'use case' and 'constraints' but does not explain the nested constraints structure, the meaning of limit, or how these parameters affect results. The description adds little beyond the parameter names.
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 a specific verb 'Recommend' and resource 'open source projects', which establishes the tool's core purpose. However, it does not distinguish itself from sibling tools like search_projects or compare_projects, so it falls short of a 5.
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 phrase 'for a concrete agent use case and constraints' implies the tool is best used when a specific use case and constraints are provided, but there is no explicit guidance on when to choose this over search_projects or compare_projects. No exclusions or alternatives are mentioned, making the guidance only moderately useful.
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 addresses a distinct stage of the workflow: search_projects finds candidates, get_project retrieves detailed knowledge, recommend_project provides tailored suggestions, compare_projects contrasts options, and get_agent_workflow guides the overall process. No two tools have overlapping purposes, making misselection very unlikely.
All tool names follow a consistent verb_noun pattern (compare_projects, get_agent_workflow, get_project, recommend_project, search_projects). The two 'get_' tools are clearly differentiated by their objects (agent_workflow vs project), maintaining uniform style and predictability.
Five tools is well within the ideal 3-15 range and perfectly scoped for a project discovery and comparison server. Each tool earns its place, covering search, retrieval, recommendation, comparison, and workflow guidance without redundancy or bloat.
The tool set covers the full user journey: discovering projects via search, getting in-depth information via get_project, obtaining personalized recommendations, comparing alternatives, and following a structured analysis workflow. No obvious gaps exist for the platform's stated purpose.
