USE WHEN you have a specific operatorId + capability and want the full machine-readable profile (inputs, outputs, pricing, approval-required flag, endpoint). Pre-flight check before chieflab_create_work_request.
| Name | Required | Description | Default |
|---|---|---|---|
| capability | Yes | ||
| operatorId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the tool returns a 'full machine-readable profile' and lists fields, implying it is read-only and non-destructive. However, it does not disclose authorization needs, side effects, or potential issues. Adequate for a simple get operation but could be more 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 extremely concise with only two sentences. It is front-loaded with the usage condition and clearly states the purpose. Every sentence adds value with no wasted words.
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's simplicity (2 params, no output schema), the description is fairly complete: it explains when to use, what it does, and what to expect. It lacks detail on error handling or parameter validation, but overall it provides sufficient context for an agent.
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 must compensate. It mentions 'operatorId + capability' but does not define their format, constraints, or provide examples. The schema only specifies type string with no descriptions, leaving ambiguity about what values are valid.
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 verb 'get' and resource 'capability', specifies the exact inputs (operatorId + capability), and lists the returned information (inputs, outputs, pricing, etc.). It distinguishes itself from sibling tools like chieflab_create_work_request by positioning itself as a pre-flight check.
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 explicit guidance: 'USE WHEN you have a specific operatorId + capability.' It also notes the tool is a pre-flight check before chieflab_create_work_request, giving clear context. It does not explicitly mention when not to use or alternatives like search_capabilities, but the guidance is still strong.
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.
Most tools have distinct purposes, e.g., approve_action vs execute_approved_action vs publish_approved_post. However, alias overloading (e.g., chieflab_launch_product and chieflab_get_users_after_build pointing to the same handler) introduces some ambiguity. The detailed descriptions mostly mitigate confusion, but an agent might still struggle to choose between near-identical aliases.
Tools predominantly follow a 'chieflab_verb_noun' pattern (e.g., chieflab_approve_action, chieflab_connect_provider). A few exceptions exist (chieflab_help, chieflab_inbox, chieflab_boot) that are single nouns, but these are clearly distinct and the overall consistency is high.
32 tools is on the high side for an MCP server, but the domain of a growth/marketing launch platform naturally requires many operations (launch, approve, execute, measure, iterate, connect providers, etc.). The count is borderline but still manageable; it doesn't reach the 50+ extreme.
The tool set covers the full launch lifecycle: create, approve, execute, measure, and iterate. It includes provider connections, manual fallback, brain summary, and work requests. Minor gaps exist (e.g., no explicit tool for deleting a launch or revoking approval), but core workflows are fully supported.