get_fundamentalsRetrieve analysis-ready fundamental metrics for any DSE-listed symbol, including EPS, P/E ratios, dividend yield, reserves, market cap, and 52-week range.
Analysis-ready fundamentals: EPS, P/E (interim/audited/trailing), dividend yield + latest dividend, reserves, market cap, 52-week range.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does 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 does reveal the specific output metrics and notes nuanced P/E categories, but it does not state whether this is a read-only operation, what happens on invalid symbols, data freshness, or any other behavioral caveats. The metric detail adds some transparency, but not enough for a fully unannotated tool.
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 a single, tightly written sentence that front-loads the value proposition ('Analysis-ready fundamentals') and then itemizes the specific data points. There is no redundancy or filler.
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?
The tool is simple with one required parameter and an output schema exists, so the description does not need to explain return structures. The metric list gives enough context for basic invocation. Missing usage differentiation and behavioral caveats are covered by other dimensions, so this remains 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 schema has 0% description coverage and the description does not mention the sole 'symbol' parameter at all. While 'symbol' is conventional, the description adds no meaning about expected format, normalization, or valid values, which the low coverage requires.
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 as 'analysis-ready fundamentals' and enumerates the exact metrics included (EPS, P/E variants, dividend, reserves, market cap, 52-week range). It is distinguishable from sibling tools like get_quote or get_pe_ratios, though it does not explicitly call out those distinctions.
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 metric list: an agent can infer this is the tool to call when needing fundamental data points. However, there is no explicit guidance on when to prefer this over overlapping siblings such as get_pe_ratios or get_company_profile, and no exclusionary context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.