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Glama

explain_price_move

Read-onlyIdempotent

Show the facts behind a stock's daily price move: its return versus the benchmark, relative size and volume, ex-dividend status, and dated news—without stating causes or predictions.

Instructions

For "why did it rise or fall today?": the facts around one session. The stock's move next to the benchmark index's move that day and the difference between them, how large the move and the volume were against the stock's recent days, whether it was an ex-dividend day, and news or disclosures from the day before to the day after, with their dates. Present these side by side; never apportion the move to the market or the company, never state its cause, never predict. Without a date, it describes the latest completed session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoISO date of the session; defaults to the latest session.
symbolYesA symbol returned by search_assets.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.9

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish safe read semantics (readOnly, idempotent, openWorld). The description adds substantial value beyond that by disclosing the output contract (facts presented side by side) and firm interpretive constraints (never apportion, never state cause, never predict), which prevent the agent from over-claiming. It does not cover things like rate limits or result shape beyond content, but the interpretive guardrails are the important disclosure here.

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 usage trigger is front-loaded and every clause (the enumerated facts plus the three 'never' constraints) earns its place. It is a single dense run-on sentence, which is the only structural blemish.

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?

With no output schema, the description carries the return-content burden and does so thoroughly, listing the facts returned and the default-date rule. Combined with annotations covering safety, an agent has enough to call it correctly; only finer output formatting is absent.

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 coverage is 100%: both 'date' and 'symbol' are documented, with symbol already pointing to search_assets in the schema. The description only echoes the default-session behavior for date, adding nothing the schema lacks, so baseline 3 is correct.

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?

States a specific verb+resource ('explain_price_move') and enumerates exactly the facts it assembles: the stock's move vs the benchmark's, the spread, size and volume vs recent days, ex-dividend status, and surrounding news. This precisely delineated scope (one session, facts only) implicitly separates it from neighbors like compare_assets or get_price_summary.

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?

Opens with an explicit trigger ('For "why did it rise or fall today?"') and clarifies the default-date behavior. It does not name an alternative tool or state when-not to use it, so it stops short of full routing guidance.

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