get_gex_profile
Per-strike GEX profile near spot.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | No | SPY |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Per-strike GEX profile near spot.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | No | SPY |
| 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?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it only states what the output is about. It does not mention read-only nature, default symbol behavior, how 'near spot' is defined, or what happens when data is unavailable—though the output schema does cover return shape, the description adds no behavioral context.
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 and front-loaded, with no wasted words. However, it is arguably too terse: it is only a noun phrase, not a full sentence, and omits information that would help an agent use the tool correctly. It earns its keep as a summary but not as a complete instructional description.
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?
The existence of an output schema covers return-value structure, and the single optional symbol parameter lowers complexity. But the description leaves key contextual gaps: what 'near spot' means, how the symbol parameter interacts with the profile, and when this tool should be preferred over siblings. For a tool with no annotations and no parameter descriptions, this is insufficiently complete.
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 has one parameter, 'symbol', with no description, and schema description coverage is 0%. The tool description does not mention the symbol parameter, its default value, or how it affects the returned profile. The meaning of the parameter is entirely left to inference from the tool name and default value.
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 'Per-strike GEX profile near spot' identifies a specific resource (a GEX profile) and implicitly the action (retrieve/get), and the GEX-specific wording helps distinguish it from the many other get_* siblings. However, it lacks an explicit verb and does not clarify what 'near spot' precisely means, leaving minor ambiguity.
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 gives no guidance on when to use this tool versus the many sibling tools such as get_skew or get_path_risk_score. There is no mention of use cases, exclusions, or alternatives. It is not misleading, but it offers no usage direction.
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 metric or workflow—alert checks, alert lists, gamma maps, volatility indices, replay timelines, execution plans—so an agent can reliably pick the right one from its description. Even the alert-related tools (get_latest_alert, list_alert_history, check_alert_tradeable) have clearly separate outputs.
All tool names follow a consistent verb_noun snake_case pattern (mostly get_, plus check_, format_, list_, plan_). This makes the set predictable and easy to scan.
At 32 tools, the surface is heavy and approaches a disorganized collection of endpoints rather than a curated set. Many individual get_* indicators could be grouped into a smaller number of dashboard or snapshot tools without losing clarity.
The server covers the core 0DTE intelligence lifecycle: alerts, historical replays, risk overlays, structure, gamma, volatility, news, and advisory planning. Minor gaps exist—such as a direct quote or option chain feed—but they are not essential to the stated purpose.