Compose a candidate open-source AI stack and expose unknown compatibility.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | en | |
| request_id | No | ||
| constraints | No | ||
| business_goal | Yes | ||
| existing_stack | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds 'candidate' and 'unknown compatibility', but does not explain what the tool does with constraints or existing_stack, nor what 'exposing compatibility' concretely means.
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 filler. However, the trailing phrase 'and expose unknown compatibility' is unclear and could have been worded more precisely without adding length.
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?
With five parameters, no schema descriptions, and only a vague sentence, the description does not give the agent enough to know how to construct inputs or interpret the output. It lacks guidance on required business_goal, how constraints influence the result, or what 'unknown compatibility' means.
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 0%, so the description needed to compensate by explaining business_goal, constraints, existing_stack, locale, and request_id. It does not; it only broadly indicates that an AI stack is composed. The parameter names are somewhat self-explanatory, but the description adds virtually no parameter-level meaning.
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 states a specific action ('Compose a candidate open-source AI stack'), which clearly identifies the tool's main resource and distinguishes it from the sibling browsing/comparison/search tools. However, the phrase 'expose unknown compatibility' is vague and does not clearly define what is exposed or how.
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?
No guidance is provided about when to use this tool versus alternatives, and there are no exclusions or conditions. The agent must infer from the name and context that this is for composing a stack rather than browsing, comparing, or searching.
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 generally distinct role: browsing radar views, searching projects, getting facts, comparing, composing stacks, and finding alternatives. A couple of tools—notably browse_radar_projects and search_ai_projects—could be confused, but their descriptions clarify exploratory browsing versus requirement-driven search.
All tool names follow a consistent snake_case verb_noun pattern: browse_*, get_*, search_ai_projects, compare_ai_projects, compose_ai_stack, find_alternatives. The naming makes the action and target object immediately clear across the entire set.
Nine tools is a well-scoped size for an open-source AI intelligence and decision-support server. Each tool covers a distinct part of the workflow without feeling bloated or redundant.
The set covers the main workflow well: overview, browsing, search, project facts, license evidence, comparison, stack composition, and alternatives. Minor gaps like project tracking/history or export utilities are non-essential for this kind of intelligence/decision-support surface.