Get historical derived metrics (TTM aggregates + margins per period).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | Yes | ||
| frequency | No | quarterly |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only explains the output (TTM aggregates + margins per period) but does not state side effects, idempotency, authorization needs, or rate limits. For a tool that queries historical data, it is assumed safe but not confirmed.
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 sentence with no filler, making it concise. It front-loads the core action and output. However, it could be slightly improved by clarifying 'derived metrics' or adding a brief note on parameter defaults.
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 complexity of historical metrics and the presence of many sibling tools, the description is incomplete. It neither explains what 'TTM aggregates' means nor how parameters like 'frequency' affect results. The output schema exists but is not shown, so the description alone does not equip the agent adequately.
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%, and the description does not explain any parameters. 'limit', 'ticker', and 'frequency' are undefined in the description. The agent must infer their meaning from the tool's name and context, which is insufficient.
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 states 'Get historical derived metrics (TTM aggregates + margins per period)', which indicates the tool retrieves historical financial metrics. However, 'derived metrics' is vague without further explanation, and the description does not differentiate from siblings like 'get_metrics' (likely current) or other historical tools like 'get_balance_sheet'.
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?
No explicit guidance on when to use this tool versus alternatives. The implied use case is for historical derived metrics, but there is no mention of when to prefer this over 'get_metrics' or avoid it for non-derived data. Lack of context for the 'frequency' and 'limit' parameters also hampers correct usage.
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.
Each tool targets a distinct financial data aspect (e.g., balance sheet vs income statement vs cash flow; different holding types; metrics vs history). No overlapping purposes.
All tools follow verb_noun pattern with snake_case (e.g., get_balance_sheet, compare_metrics). Consistent and predictable.
19 tools is slightly above the typical 3-15 range but covers a broad domain (statements, metrics, holdings, screening). Still reasonable and well-scoped.
Covers most key financial data needs: statements, metrics, insider trades, institutional holdings, screen/search. Minor gaps like earnings estimates or dividend history are absent but core workflows are complete.
