Side-by-side log-returns for up to 5 tickers — stocks, ETFs, crypto. Volatility, total return, max and min. Date-aligned.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Default 1Y | |
| tickers | Yes | List of 2-5 tickers, e.g. ['AAPL', 'MSFT', 'NVDA'] |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by disclosing the log-return methodology, date-aligned processing, and asset class scope. It does not detail return format, but annotations lower the burden for safety-related traits.
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 exceptionally concise—three short fragments that front-load the core action and key output metrics. No redundant words; every clause contributes meaningful information.
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?
With no output schema, the description compensates by naming the output metrics (volatility, total return, max/min) and highlighting date-alignment. The schema covers the period default, so this is reasonably complete for a read-only comparison tool, though it could mention handling of missing data.
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 100%: tickers and period are fully documented in the schema including min/max items and enum values. The description adds no new parameter-specific meaning beyond what the schema provides, so the baseline of 3 is appropriate.
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 states the tool's function: side-by-side log-returns for up to 5 tickers across stocks, ETFs, and crypto. It lists specific computed metrics (volatility, total return, max/min), making it distinguishable from sibling tools like get_close_history or get_price_alignment.
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?
The description implies usage when comparing multiple tickers and specifies the 2-5 ticker constraint. However, it does not explicitly mention when to prefer this tool over alternatives or any exclusions, leaving the agent to infer based on purpose.
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.
With 57 tools, most have distinct purposes (market data, journaling, watchlists). A few related tools (get_price_alignment vs get_crypto_price_alignment, get_market_pulse vs get_market_movers) could cause miselection, but descriptions clarify asset types and scope.
Tools predominantly use get_/list_/create_/update_/delete_ verbs with clear noun suffixes. Minor deviations like start_here, whoami, add_to_watchlist, and remove_from_watchlist break the pure verb_noun pattern, but the style is consistent and readable.
At 57 tools, the server is far beyond the well-scoped range. While the domain is broad, this many tools will overwhelm an agent's capability to select accurately, and many could be consolidated (e.g., separate financial statements).
The server covers watchlist CRUD, trading journaling, market data (fundamentals, statements, news, transcripts), analysis tools, and community features. No obvious dead ends; lifecycle coverage is thorough for the described domain.
