list_modelsThe valuation models saved to this MarketPing account (Models: DCF, excess return, sum of parts), with the company and a link. Needs a linked account. Optional company narrows to one company (slug). Factual data only — MarketPing publishes no buy/sell recommendations, no price targets and no IPO grey-market premium.
| Name | Required | Description | Default |
|---|---|---|---|
| company | No | Company slug to narrow to (optional) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: the account-link prerequisite and the factual-data-only policy with no recommendations, price targets, or grey-market premium. No contradiction found.
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?
Four concise sentences, with the core purpose and model types front-loaded. The factual-data-only clause adds a relevant boundary rather than fluff.
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?
Even without an output schema, the description sketches the output (company and link), the account prerequisite, filtering behavior, and data-policy constraints. This is sufficient for a simple list tool, though the return shape is only lightly described.
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 coverage is 100%, and the schema already documents `company` as an optional slug to narrow by. The description reinforces this by saying it narrows to one company, but adds little new format or behavior detail beyond the schema.
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 identifies the resource: saved valuation models on the MarketPing account, with model types and output elements (company, link). It does not use an explicit verb like 'lists' or 'returns', and it doesn't contrast with sibling run_model, so it misses the top tier.
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?
It gives actionable context: a linked account is required, and the optional company parameter narrows to a single company. However, it doesn't mention alternatives or when not to use this tool, so it stops short of explicit routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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