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0DTE Confluence

get_daily_structure

Daily Structure Board: automated pivots, ATR targets, overnight boundaries. Bundle tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoSPY

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

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether this is a read-only retrieval, how the 'board' is structured, whether access or subscription constraints apply, or what operational behavior the agent should expect despite the 'Bundle tier' fragment.

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?

The description is appropriately short and front-loads the core contents. The trailing 'Bundle tier.' is cryptic and adds little operational value, but it does not bloat the overall description.

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?

With no annotations, no parameter guidance, and no usage context relative to similar get_* tools, the description is not sufficient for an agent to confidently select this tool over get_swing_structure or get_market_clock. The output schema helps with return value shape, but the intended context and access implications are left unclear.

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%, and the description never mentions the symbol parameter or its SPY default. The agent must rely entirely on the property name and default, while the description adds no semantic value to parameter understanding.

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?

The description names the resource as a 'Daily Structure Board' and enumerates concrete contents: automated pivots, ATR targets, and overnight boundaries. This goes beyond a tautology and gives the agent a clear sense of what the tool provides, though it does not explicitly distinguish it from sibling tools like get_swing_structure.

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

Usage Guidelines3/5

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

The word 'Daily' and the listed contents imply the tool is relevant when an agent needs daily pivot, ATR, or overnight-boundary context. However, there is no explicit when-to-use guidance, no exclusions, and no mention of alternative tools, so usage must be inferred rather than stated.

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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