get_equity_fundamentalsEquity fundamentals — financials, growth, margins, valuation (P/E, EV/EBITDA, FCF yield, ROIC), peers.
| Name | Required | Description | Default |
|---|---|---|---|
| peers | No | ||
| frequency | No | quarterly | |
| identifier | Yes | ||
| year_history | No | ||
| force_refresh | No | ||
| identifier_type | No | ticker |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful detail about the returned data scope (P/E, EV/EBITDA, FCF yield, ROIC, peers), but it does not disclose behavior around refresh, data history, or limitations. This is adequate given the annotation coverage.
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 scannable sentence with a specific list of valuation metrics and data categories. It is concise and front-loaded, with no filler, though the opening 'Equity fundamentals' largely restates the tool name.
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 six parameters and zero schema descriptions, the description is too sparse to fully support correct invocation. The output schema and annotations help, but the description does not explain required inputs, optional parameter behavior, or how this relates to other market-data tools. It is adequate for selection but incomplete for confident use.
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%, so the description must compensate, but it only mentions 'peers' as a concept. The meanings and formats of identifier, identifier_type, frequency, year_history, and force_refresh are not explained anywhere in the description. This leaves the agent guessing on multiple parameters.
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 identifies the resource (equity fundamentals) and lists concrete content categories: financials, growth, margins, valuation metrics, and peers. It is clear enough for an agent to know what kind of data this tool provides, though it does not explicitly differentiate itself from market-data siblings like get_market_data or get_recent_results.
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 guidance is provided about when to use this tool instead of alternatives. The content list implies it is for fundamental analysis, but there is no explicit statement of appropriate context, exclusions, or comparisons to sibling tools.
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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Most tools are distinct, but several pairs overlap in purpose: get_market_data and list_watchlist both return watchlist prices/signals, and the four 'brief' tools have fuzzy boundaries. Descriptions help, but an agent could easily select the wrong one without deeper context.
The dominant verb_noun pattern (get_* for details, list_* for collections) is clear and consistent in style. There are minor deviations like lookup_index_by_brand and run_technical_analysis, and several plural collections use get_, but these remain readable and mostly predictable.
39 tools is well past the 25+ threshold and represents a heavy surface for an agent to navigate. The broad wealth domain explains some of the count, but many granular getters could be consolidated or curated.
The set covers the advertised wealth surface well—portfolio, risk, credit, real assets, markets, geopolitics, watchlist, goals, family, and documents—but it is read-only and lacks obvious navigation endpoints like list_portfolios or detail views for goals/alerts. Agents can retrieve most data, but not all lifecycle operations or entity enumerations are present.