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format_bracket_plan

Scale/stop premium levels from fill price E (+25% target, -25% cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alert_jsonNo
use_latestNo
entry_premiumYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral disclosure burden, but it only reveals the +/-25% rule. It does not disclose whether this is a pure calculation, whether it modifies any state, how alert_json or use_latest influence behavior, or what kind of output is returned beyond 'levels'.

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

Conciseness3/5

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

The description is short and packs the threshold percentages into one sentence, but the unexplained 'E' and the ambiguous 'scale/stop' phrasing create avoidable confusion. Conciseness is achieved at the expense of clarity, so it is only marginally acceptable.

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

Completeness2/5

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

Although an output schema exists, the description fails to explain how the inputs map to the computation, lacks any annotation context, and omits usage guidance. For a tool with three parameters and one required field, this is insufficient for reliable invocation.

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

Parameters2/5

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, but it only obliquely hints at entry_premium through 'fill price E'. alert_json and use_latest are completely unaddressed, leaving most of the parameter semantics unspecified and forcing the agent to guess.

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

Purpose3/5

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

The description states a specific operation on a resource ('Scale/stop premium levels') and gives concrete thresholds (+25% target, -25% cap), so it is not a tautology. However, the verb phrase 'scale/stop' is ambiguous, and the symbol 'E' is unexplained, leaving the tool's overall purpose vague for an agent without domain-specific context.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives like plan_robinhood_entry or other alert-related siblings. The description does not state prerequisites, exclusions, or a decision context, so an agent must rely on the name alone.

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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TDQS

B3/5.0
Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count2/5

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.

Completeness4/5

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.

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