Return SIEM-ready detections for agentic AI and MCP telemetry.
| Name | Required | Description | Default |
|---|---|---|---|
| rule_id | No | ||
| decision | No | ||
| severity | No | ||
| event_class | No | ||
| workflow_id | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that the tool returns detections, with no mention of side effects, read-only behavior, authentication requirements, filtering behavior, or what 'SIEM-ready' means operationally. This is not contradictory, but it is far too thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no wasted words, and the key outcome is front-loaded. However, it is under-specified for a tool with five parameters and no annotations, so brevity comes at the cost of useful operational detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema existing, the definition omits all parameter semantics, usage conditions, and behavioral context. With 0% schema coverage and no annotations, this one-line description is not enough for an agent to reliably select and invoke the tool across the large sibling set.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any of the five parameters (rule_id, decision, severity, event_class, workflow_id). There is no compensation for the schema gap, so an agent has no guidance on what values these parameters take or how they affect the returned detections.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Return') and a concrete resource ('SIEM-ready detections for agentic AI and MCP telemetry'), so the core purpose is clear. It does not explicitly distinguish this from siblings like recipes_agentic_incident_response_pack or recipes_agentic_action_runtime_pack, but the 'SIEM-ready detections' focus gives reasonable differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus any of the many sibling recipe packs. No alternative tools are named, no conditions for selection are given, and no exclusions are stated. An agent would have to infer usage from the tool name and one-line description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools return 'pack' artifacts with nearly identical descriptions, such as recipes_agentic_assurance_pack, recipes_agentic_posture_snapshot, and recipes_agentic_readiness_scorecard, or recipes_mcp_connector_intake_pack versus recipes_mcp_connector_trust_pack. Distinct domains like CVE lookup and playbooks are clear, but dozens of evidence/profile packs blur together and will cause misselection.
All names use the recipes_ prefix and snake_case, and most pack tools follow a [domain]_[topic]_pack pattern, which aids recognition. However, verbs are placed inconsistently and mixed with noun-only names: recipes_get, recipes_cve_get, recipes_mcp_server_get, recipes_refresh, and many pure 'pack' names.
Seventy-five tools is an extreme count for any MCP server, especially when the majority are highly specialized 'pack' endpoints with narrow outputs. The sheer number creates major selection overhead and makes the tool surface difficult for an agent to navigate reliably.
The server covers its apparent read-only scope thoroughly: recipe search/get, CVE lookup, playbook planning, MCP server catalog, upstream MCP introspection, and extensive evidence packs. There are no obvious dead ends, though the massive pack proliferation makes it harder for agents to know which tool to call.