Skip to main content
Glama
DinevDecor

Signal Feed API: market regime for agents

get_results_record

Retrieve full daily paper trading results for each indicator, including equity, returns, benchmark, exposure, drawdown, and losses. Filter by indicator ID to audit performance.

Instructions

Full daily PAPER results of the virtual account behind each indicator (equity, return, benchmark, exposure, flat days, weekly fees and drawdown), losses included. Optional indicator id filter.

Input Schema

NameRequiredDescriptionDefault
indicatorNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden, and it does disclose meaningful behavior: results are for a simulated 'PAPER' account, contain one record per day, and explicitly include losses (i.e., no filtering of negatives). It says nothing about permissions, pagination, date ranges, or volume of results, which matters for an unfiltered daily series.

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?

Two sentences, front-loaded with what the tool returns and ending with the filter behavior. The parenthetical metric list is dense but earns its space by telling the agent what fields to expect.

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?

An output schema exists, so return values need not be re-explained, and the single parameter is covered. What remains missing is scale/pagination context and any routing signal versus siblings, both minor for a one-parameter read tool.

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 0% for the single 'indicator' parameter, but the description does explain that it is an optional id filter, implying omission returns results for all indicators. It never states the identifier format or what happens with an invalid id, so it only partly compensates for the schema gap.

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 the specific resource clearly: full daily results of the virtual (paper) account behind each indicator, and enumerates the metrics returned (equity, return, benchmark, exposure, flat days, weekly fees, drawdown). An agent knows exactly what data comes back, but the description never distinguishes it from siblings like get_deviations or get_latest_issue.

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?

The only usage hint is 'Optional indicator id filter'; there is no guidance on when to call this versus get_deviations or get_latest_issue, and no mention of prerequisites or typical workflow. The agent must infer usage from the resource name alone.

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