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InsiderEU

get_rebound_panics

Get today's Rebound Radar alerts. These are global blue-chip stocks that dropped >5% on volume and were evaluated by GPT-4 for overreactions. Use this to find 'ACUTE_SHOCK' or 'OPERATIONAL_FRICTION' buying opportunities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
playbookNoOptional filter by GPT-4 classified playbook.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose meaningful behavior: the data is scoped to today, the universe is global blue-chip names, and inclusion requires a >5% volume-backed drop plus GPT-4 overreaction classification. It does not say anything about result size, ordering, freshness beyond 'today', or permissions, so the behavioral picture is partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the core action and with no filler. The middle sentence is dense but earns its place by defining the alert criteria; overall tight and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-optional-param read tool with no output schema, the description covers what the data is, how it was generated, and how to use it. The main remaining gap is the shape and volume of the returned alerts, which an agent would have to discover by calling it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single optional param already carries its own description, so the schema does the heavy lifting. The description adds the framing that the two enum values are buying-opportunity categories, which is mild extra meaning but not new filtering semantics such as what happens when the filter is omitted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get today's Rebound Radar alerts') and goes further by defining what the alerts actually are: global blue-chip stocks that dropped >5% on volume and were GPT-4 evaluated. That makes the tool's domain concrete, though it never names or distinguishes itself from the similarly-named sibling get_radar_pro_alerts or get_cluster_buys.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use this to find ACUTE_SHOCK or OPERATIONAL_FRICTION buying opportunities' gives a clear context for when to reach for this tool and ties it to the enum values. There are no stated exclusions or routing rules against the other alert-style siblings, so it stops short of full alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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