Return adversarial drills for agentic remediation workflows and MCP controls.
| Name | Required | Description | Default |
|---|---|---|---|
| scenario_id | No | ||
| workflow_id | No | ||
| attack_family | 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?
Annotations are absent, leaving the description as the sole source of behavioral disclosure. It implies a read-only generation action by saying 'Return', but it doesn't state whether the tool has side effects, requires authentication, or what the output structure is. The description does not add context beyond the action itself, and the existence of an output schema isn't referenced here.
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 short sentence with no wasted words, and it gets to the point immediately. However, it is so terse that it borders on under-specification; it would be more effective if it front-loaded a bit of parameter context. Yet as conciseness goes, it is efficient.
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?
For a tool with three optional parameters and an output schema, the description is not complete. It doesn't explain what a 'drill pack' is, how the parameters refine the result, or what the returned adversarial drills contain. The agent is left guessing at the input semantics and expected output, making successful invocation uncertain.
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?
The description has 0% schema coverage and mentions none of the three parameters (scenario_id, workflow_id, attack_family). Since the schema gives only names and types, and the description doesn't explain how these affect the returned drills, an agent has no sense of how to set these fields.
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 states a concrete action ('Return') and a specific resource ('adversarial drills for agentic remediation workflows and MCP controls'), which gives the agent a clear sense of what it will deliver. It stops short of a full 5 because it doesn't contrast with the many sibling red-team tools (e.g., recipes_agentic_red_team_replay_harness) or clarify the exact boundaries of 'agentic remediation' scope.
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 dozens of recipe siblings. No conditions, alternatives, or exclusions are offered, so an agent must infer when this is the right choice, which is risky given the large, highly overlapping toolset.
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.