get_option_pressureOption-chain pressure map for the nearest weekly/monthly expiry — Max Pain, dealer Gamma Wall, likely weekly high, and an extreme squeeze target.
Args:
ticker: Stock symbol, e.g. "SPY".
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond annotations, listing specific output metrics (Max Pain, Gamma Wall, weekly high, squeeze target). Annotations already indicate safe, read-only, idempotent behavior, so the description complements them without contradiction.
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 extremely concise (2 sentences plus parameter docstring), front-loaded with the main purpose, and contains no superfluous 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?
Given the tool's simplicity (1 parameter, no output schema, rich annotations), the description fully covers what the tool returns and what input it needs, leaving no significant gaps.
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?
With 0% schema description coverage, the description provides necessary parameter semantics: 'ticker: Stock symbol, e.g. 'SPY'.' This adds meaning beyond the schema's type-only definition, though it could include additional constraints (e.g., valid exchanges).
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 purpose: returning an option-chain pressure map for the nearest weekly/monthly expiry, including specific metrics like Max Pain and Gamma Wall. It differentiates from sibling tools like get_iv_radar by focusing on pressure map calculations.
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 near-term expiries ('nearest weekly/monthly expiry') but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites.
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.
Every tool has a clearly distinct purpose, from individual analytics like AI prediction and IV radar to aggregation and report generation. No overlapping functionality.
All tool names follow a consistent verb_noun pattern using snake_case, with verbs like get_, generate_, and analyze_. No mixing of conventions.
9 tools is well-scoped for a quant finance server, covering diverse analytics and outputs without being excessive or sparse.
Covers major quant finance analyses and reporting. Minor gap: no raw data access tools, but the surface is comprehensive for the intended use case.