Real-Time CVD Liquidity Tracker: aggregate Net CVD using Lee-Ready on minute bars. Pro tier. interval: "1m" | "5m"
| Name | Required | Description | Default |
|---|---|---|---|
| interval | No | 1m | |
| instrument | 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?
No annotations are provided, so the description carries the full behavioral disclosure burden. It does disclose that the tool provides real-time data, uses Lee-Ready logic, and supports 1m/5m intervals, but it leaves unclear what 'Pro tier' implies and whether the result is a snapshot or a series.
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 compact and front-loaded with the core method and metric. The 'Pro tier. interval: 1m | 5m' portion is terse and slightly awkward, but there is no redundant filler.
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 an output schema exists and the tool has only two simple parameters, the description is reasonably complete for basic invocation. However, it fails to mention the instrument parameter, potential default behavior, or how this tool fits among related liquidity and order-flow tools.
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. It documents the allowed interval values ('1m' | '5m') but completely omits the instrument parameter, which is a significant gap given the schema provides no descriptions either.
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 operation: it aggregates Net CVD using Lee-Ready on minute bars, which is a specific and distinctive computation. It does not explicitly contrast itself with sibling tools like get_order_flow or get_liquidity_concentration, but the unique CVD focus makes the purpose recognizable.
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 does not say when to use this tool versus alternatives such as get_order_flow or get_liquidity_concentration. It only notes 'Pro tier' as a possible access constraint, which is not usage guidance.
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.