Look up a US-listed company's real SEC 10-K financials and compute Graham fair value, margin of safety, P/E, P/B, ROE, current ratio, debt/equity, and dividend yield. Every number is pulled directly from the company's own XBRL-tagged filing -- there is no LLM in the numeric path, so nothing here is a guessed or hallucinated figure.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | US stock ticker symbol, e.g. AAPL, KO, MSFT |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does disclose an important trait: every figure comes from the company's own XBRL-tagged filing with no LLM in the numeric path, so outputs are deterministic and not hallucinated. It stops short of failure modes (invalid ticker, missing/non-10-K filings), latency, or coverage limits.
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?
Two sentences, front-loaded with the action and resource, followed by a provenance guarantee that earns its place by addressing the main trust concern for financial data. Some list-weight in the metric enumeration, but it doubles as an implicit output description.
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?
No output schema exists, and the description compensates by enumerating the metrics returned; the single required parameter is fully documented in the schema. It lacks error/edge-case behavior, which keeps it from being fully complete for a data-fetch tool.
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 there is only one required parameter, so the baseline is 3. The description adds no syntax or format detail beyond what 'US stock ticker symbol, e.g. AAPL, KO, MSFT' already provides.
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?
States a specific verb (look up) and resource (SEC 10-K financials) plus the exact derived metrics it computes (Graham fair value, margin of safety, P/E, P/B, ROE, current ratio, debt/equity, dividend yield). An agent knows precisely what this returns without opening the schema.
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?
Usage is implied by the scope language ('US-listed company', 'SEC 10-K'), which implicitly excludes non-US issuers and non-10-K filers, but the description never states when to use this versus other sources or any prerequisites/exclusions explicitly. No siblings exist to route against, so the gap is modest.
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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