Skip to main content
Glama

Get a research report

get_research
Read-onlyIdempotent

Retrieve one of YOUR previous research reports. Others' runs are simply not found.

    Args: research_id — the identifier `run_research` returned when it started that run.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
research_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNo
as_ofNo
errorNo
risksNo
stepsNo
promptNo
reasonNo
statusNo
blockedNo
query_idsNo
complianceNo
limitationsNo
research_idNo
schema_versionNo
proposed_actionsNo
not_investment_adviceNo

TDQS

A4.5/5.0
Behavior4/5

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

Beyond the readOnly/idempotent annotations, the description adds meaningful behavioral context: the report must be from the caller's own run, and other users' reports will simply not be found. It also explains the provenance of the research_id, which informs how the tool behaves when given an invalid or foreign ID.

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?

Two compact sentences carry the behavior, scope, and parameter semantics with no filler. The key constraint ('YOUR previous research') is front-loaded, and the argument explanation is immediately actionable.

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?

For a simple single-ID read operation, the description, combined with strong annotations and an output schema, leaves no critical gap. The agent knows what to call, how to obtain the identifier, and what to expect in terms of access scope.

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?

Schema description coverage is 0%, so the description must compensate. It does by explaining that research_id is the identifier returned by run_research at the start of a run, giving the agent a concrete way to source the value. It stops short of providing format examples, but the provenance guidance is highly useful for a single-parameter tool.

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?

Description uses a specific verb ('Retrieve') and identifies the exact resource: the user's own previous research reports. It clearly distinguishes itself from run_research by focusing on past reports, and even notes that others' runs are not found, which sharpens the scope.

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?

The description clearly implies this tool is for retrieving already-created reports, not for running new research. It references run_research as the source of the identifier, which gently points toward the workflow without explicitly listing when-not-to-use alternatives.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

The tools are largely distinct: querying, searching, backtesting, risk reads, alerts, memory, and audit functions each have clear homes. A few adjacent pairs (risk_read vs risk_assess, company_health_check vs positioning_read) could be confused, but the descriptions draw explicit boundaries.

Naming Consistency3/5

There are strong consistent clusters like list_*, get_*, run_*, and memory_*, but the *_read suffix alternates with noun-first names like company_health_check, and bare-verb tools like ask, calendar, chart, and screen break the pattern. The naming is readable but not uniform.

Tool Count2/5

Forty tools is well past the 25+ threshold and makes the surface heavy for an agent to navigate, even though the breadth reflects a genuinely wide platform. Several clusters could plausibly be consolidated without losing capability.

Completeness4/5

The tool surface covers the main lifecycle well: discovery, point-in-time querying, filings search and full text, backtesting, research, risk assessment, alerts, memory, approvals, and provenance verification. Minor gaps exist—no strategy management tools, no memory deletion, no bulk export—but agents can work around them.

Resources