Automatically organize your support tickets by priority and status to streamline your workflow. This tool generates a status summary, sorts tickets by importance, and identifies high-priority open tickets that need an assignee. (reference price: $0.0000 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. It describes the output (summary, sort, identification) but does not disclose whether the tool modifies ticket data, what permissions are needed, or any side effects. The price reference is present but does not add behavioral insight.
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 short (two sentences plus a price note) and front-loaded with the main action. However, the brevity comes at the cost of missing critical details about the input parameter and usage, making it incomplete rather than efficiently concise.
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 input parameter with no description and no usage guidelines, the description is insufficient for an agent to invoke it correctly. The presence of an output schema somewhat helps, but the agent cannot determine what to pass as payload. The tool's overall context is only partially addressed.
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 does not explain the single 'payload' parameter at all. The parameter is a free-form object with no hints, and the description implies the tool works automatically but gives no indication of what input is expected or how to provide ticket data.
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 the tool generates a status summary, sorts tickets by importance, and identifies high-priority open tickets needing an assignee. This is a clear purpose with a specific verb and resource, though the tool name includes 'friction' which may cause confusion. It does not explicitly differentiate from siblings, but the functionality is unique among the listed siblings.
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 other tools, nor does it mention any prerequisites or exclusions. It simply states what it does without context for agent decision-making.
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.