Add a Subscriptions tab in user settings, a repetitive task that could be automated with a tool. (reference price: $0.0100 per call)
| Name | Required | Description | Default |
|---|---|---|---|
| payload | 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Add a Subscriptions tab', which implies a mutation operation, but it does not disclose side effects (e.g., idempotency, what happens if the tab already exists), required permissions, or any other operational behavior. The description is insufficient for an agent to understand the tool's impact.
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 concise (one sentence plus a price note), but it is not well-structured. The price reference is irrelevant to the tool's purpose and adds noise. The core sentence is front-loaded but lacks detail across other dimensions. It earns a middle score because it is short but not optimally informative.
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 tool has one parameter, no annotations, and an output schema, the description should provide enough context for invocation. It fails to describe the parameter, the effect, or the return value. The output schema exists but is not referenced. The description is incomplete for an agent to use the tool effectively.
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%, and the description makes no mention of the single parameter 'payload' or its expected format. The agent has no guidance on what to provide in the payload, making the tool effectively unusable without additional context. The description adds no value beyond the schema, which itself is empty.
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 tool's action: 'Add a Subscriptions tab in user settings'. It identifies a specific verb ('Add') and resource ('Subscriptions tab in user settings'). However, it does not differentiate from sibling tools, which are mostly friction-related and not directly comparable, so the purpose is clear but lacks explicit sibling distinction.
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 no guidance on when to use this tool versus alternatives. It mentions the task is repetitive and automatable, but that is not a usage guideline. It does not state prerequisites, when to avoid the tool, or under what conditions it should be invoked.
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.
Many tools have vague or overlapping descriptions, such as multiple 'repetitive task that could be automated' tools that lack clear differentiation. The inclusion of meta-tools (e.g., research_pain_points, develop_tools) alongside domain-specific tools further blurs boundaries, making it hard for an agent to select the correct tool.
Tool names use a mix of hyphens (add-license-information-to-codebase) and underscores (develop_tools, check_tool_health), with no consistent pattern. Some names are verbose and descriptive, while others are terse, creating an inconsistent naming convention across the set.
At 20 tools, the count is borderline but not extreme. However, the set includes several tools that are purely descriptive of problems (e.g., ai-generated-code-debugging-overhead) or are meta-tools for the factory itself, which inflates the count without adding practical utility for end users.
The server's purpose is unclear, mixing codebase operations, documentation, gamification, and support tickets. There are obvious gaps: no tool for updating or deleting, and the meta-tools (research, develop, health) are not exposed as a coherent lifecycle. The surface feels incomplete for any single domain.