Historical support and resistance price bands for one US stock, clustered from its daily bars (swing highs and lows plus volume shelves), with the nearest band above and below the latest close and how far away each sits. It describes where price HAS turned before and never forecasts whether a level will hold.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | US exchange ticker symbol, e.g. AAPL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description discloses the methodology (clustering from daily bars, swing highs/lows, volume shelves), the nature of output (nearest bands with distances), and a significant limitation (never forecasts). This gives a thorough understanding of the tool's behavior and non-behavior.
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 efficiently written with no redundant words. Each sentence adds value: it defines the output, the method, and the limitation. It is well-structured and information-dense without being verbose.
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 tool's simplicity (single parameter, no output schema), the description is complete. It explains what the tool does, how it works, what it returns, and what it does not do. There is no ambiguity about the tool's purpose or output.
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 already describes the only parameter ('ticker' as a US exchange symbol with example). The tool description adds no additional semantics about the parameter, but since schema coverage is 100% (one parameter fully described), the baseline score 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 explains that the tool provides historical support and resistance levels for a single US stock, derived from clustering daily bars, swing highs/lows, and volume shelves. It specifies the output includes nearest levels above/below the latest close with distances, and explicitly states it does not forecast. This is specific and distinguishes it from sibling tools.
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 for historical price level analysis and explicitly states it never forecasts, which guides when not to use it. However, it does not explicitly compare to alternatives or state 'use this when you need historical levels.' The 'never forecasts' is a useful usage constraint, but a direct statement about when to employ it would make it fully explicit.
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 data source or analytical angle: buybacks, congress trades, DCA fit, insider buying, 13F filings, price levels, risk phrases, and options volume. There is no overlap in purpose or output, so an agent can unambiguously select the right tool.
All tool names follow a consistent lowercase_with_underscore noun-phrase pattern (e.g., buyback_leaders, risk_filings). The naming is uniform and descriptive, making it easy to predict what each tool does based on the name alone.
The server has 8 tools, squarely in the well-scoped range. Each tool represents a meaningful, non-redundant screen or data source, and none feels like filler or duplicative functionality.
For a market-aware server, the coverage is strong: it spans corporate actions (buybacks), insider activity, institutional holdings, technical levels, risk signals, and options flow. Minor gaps exist—no general price/quote tool or earnings-focused screen—but the set is coherent and covers diverse data sources without major dead ends.