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Glama

get_schema

Read-only

Get the schema of all available fields and their valid band values. Use this when the user asks 'what fields are available?', 'what bands does momentum_rsi_zone have?', 'what sectors exist?', or when you need to validate field/band names before calling get_summary with event parameters or get_search with filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoThe TickerDB API response payload for this tool call.

Schema Changelog

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

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, establishing safety. The description adds behavioral context beyond these annotations by explaining that the tool returns field schemas and band values, and that it serves as a prerequisite validation step. It does not contradict annotations and discloses no side effects, which is appropriate.

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

Conciseness5/5

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

The description is only two sentences. The first sentence states the core purpose, and the second provides usage examples and tool relationships. Every clause adds value, with no redundancy or filler.

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

Completeness5/5

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

Given the tool has no parameters, an output schema exists, and annotations cover the safety profile, the description is highly complete. It explains what the tool does, when to use it, and how it fits into the broader workflow with other tools, leaving no critical gaps.

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

Parameters4/5

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

The tool has zero parameters, so the schema already fully documents the input (none). Per rubric, 0 params gets a baseline of 4. The description does not need to add parameter details, and none are missing.

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

Purpose5/5

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

The description begins with a clear verb+resource: 'Get the schema of all available fields and their valid band values.' This distinctly identifies the tool as a metadata/schema retrieval operation, differentiating it from sibling data-fetching tools like get_summary and get_search.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance with concrete example queries ('what fields are available?', 'what bands does momentum_rsi_zone have?') and states it should be used to validate names before calling get_summary or get_search. This gives clear when-to-use context, though it does not list exclusions, it strongly implies the tool is for schema validation and discovery.

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

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct resource/action: watchlist mutations, account info, raw candles, schema metadata, filtered searches, per-ticker summaries, and watchlist-wide summaries/deltas. The descriptions explicitly call out when to prefer one tool over another, especially get_watchlist vs get_summary vs get_watchlist_changes.

Naming Consistency5/5

Tool names follow a consistent get_* pattern for retrieval operations, with add_to_watchlist and remove_from_watchlist as clear mutating counterparts. snake_case verb_noun naming is uniform across all 9 tools.

Tool Count5/5

Nine tools is well within the ideal range and each tool earns its place. The set covers data discovery, analytics, raw data access, account management, and watchlist lifecycle without redundant or bloated surface area.

Completeness5/5

The domain of market intelligence and watchlist management is well covered: search/screen, per-ticker summaries, OHLCV data, watchlist add/remove/list, change tracking, schema discovery, and account limits. No obvious dead ends or missing core operations for the stated purpose.