Get FULL company portfolio: details, all projects, prices, reviews, contacts. Comprehensive dossier for due diligence or hiring decisions. Args: company_slug: Company slug identifier (from search results).
| Name | Required | Description | Default |
|---|---|---|---|
| company_slug | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It conveys that this is a read operation via 'Get' but does not disclose any other behavioral traits such as data volume, performance, or authorization requirements. The 'FULL portfolio' hint suggests a large response but not explicitly.
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 two sentences plus an Args section, with the primary purpose front-loaded. Every sentence adds value, and the structure is clear.
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 a single parameter and an output schema, the description covers the essential aspects: purpose, param source, and use case. It does not need to explain return values due to the output schema. It could benefit from a mention of when to use this vs. sibling tools, but overall it's adequate.
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?
The only parameter, company_slug, is clarified as 'Company slug identifier (from search results),' which adds practical guidance on where the value comes from. This compensates for the 0% schema description coverage.
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 uses the specific verb 'Get' with the resource 'FULL company portfolio' and explicitly lists the contents (details, projects, prices, reviews, contacts), making the purpose unmistakable. It also states the end-use case ('due diligence or hiring decisions'), which further clarifies intent.
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 states when to use it ('for due diligence or hiring decisions'), providing clear context. However, it does not mention any alternatives or exclusion criteria, so it lacks explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.