get_fear_greed
Intraday fear/greed composite (Tape + VIX). Fade extremes at a rail.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Intraday fear/greed composite (Tape + VIX). Fade extremes at a rail.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| 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 behavioral disclosure burden. It adds useful context by naming the inputs (Tape + VIX) and specifying the intraday timeframe, but it does not explicitly state that the call is read-only, how often it updates, or what output scale to expect, though an output schema is present.
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 one short line that front-loads the core meaning and then adds a concise usage hint. There is no filler or repetition, and every word earns its place even though 'rail' is domain-specific jargon.
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 has zero parameters and an output schema, the description provides enough context about the metric and its intraday nature to allow invocation. It could be more complete by explaining when to prefer this over related sentiment tools, but that is a usage- guidance gap rather than a critical disclosure gap.
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 input schema is empty with 100% schema description coverage, so there are no parameters for the description to clarify. The baseline of 4 applies because nothing additional is needed.
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 that the tool returns an intraday fear/greed composite composed of Tape and VIX, which identifies the resource and scope. It does not explicitly name a sibling alternative, but the metric name and qualifiers are specific enough to distinguish it from most sibling tools like get_skew or get_correlation_grid.
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 phrase 'Intraday fear/greed composite' implies use when an intraday sentiment reading is needed, and 'Fade extremes at a rail' hints at a mean-reversion trading context. However, there is no explicit guidance on when to use this tool versus the many sibling tools, nor any exclusions or conditions.
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.