Skip to main content
Glama

Recipes Agentic Threat Radar

recipes_agentic_threat_radar

Return current source-backed agentic AI threat signals and product priorities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
horizonNo
priorityNo
signal_idNo
capability_idNo
minimum_scoreNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
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 behavioral burden, yet it discloses nothing beyond the return payload. It does not say whether the call is read-only, how 'current' freshness is determined, whether results are cached, paginated, or how scores/priorities are ranked.

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?

A single front-loaded sentence with zero filler; the core action and resource appear immediately. It is efficient, though its brevity reflects under-specification rather than disciplined trimming.

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?

An output schema exists, so return-value explanation is not required, but a five-parameter filter tool with zero parameter documentation and no annotations needs far more than one sentence. The agent lacks the information needed to call it correctly or to route to the right sibling.

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% across five parameters (horizon, priority, signal_id, capability_id, minimum_score), so the description must compensate and largely does not. 'Threat signals' and 'product priorities' hint weakly at signal_id and priority, but the accepted formats for horizon, capability_id, and minimum_score are entirely undocumented anywhere.

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 states a specific verb ('Return') and a specific resource ('source-backed agentic AI threat signals and product priorities'), which is more informative than a bare name restatement. However, it does not differentiate itself from the many closely-named siblings such as recipes_agentic_exposure_graph, recipes_agentic_posture_snapshot, or recipes_agentic_source_freshness_watch, so an agent cannot tell from the text alone which of these to pick.

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?

There is no statement of when to use this tool, when not to, or which sibling to prefer for adjacent needs (e.g. freshness monitoring vs. risk registers). The agent is left to infer usage purely from the tool name.

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.