Return enterprise assurance controls, workflow evidence, and AI/Agent BOM seed.
| Name | Required | Description | Default |
|---|---|---|---|
| control_id | 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 present, and the description only says 'Return' without addressing side effects, data mutation, or permissions. It does not disclose whether the tool is read-only or has any impact on the system.
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, concise sentence with no redundant information. It is well-structured and to the point, though it could benefit from a bit more detail without becoming verbose.
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?
Given the output schema is present but not described, and the context of 'packs' is not explained, the description lacks sufficient context. It does not clarify what a pack represents or how the returned data is structured, limiting the agent's ability to use the response effectively.
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 schema defines two optional parameters (control_id, workflow_id) but the description offers no explanation of their meaning or how they influence the result. Agents cannot infer what values are expected or how they filter the output.
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 clearly states the tool returns enterprise assurance controls, workflow evidence, and AI/Agent BOM seed. This is a specific and unambiguous action, making the purpose evident.
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?
The description provides no guidance on when to use this tool versus the many sibling 'recipes_*' tools. It lacks context about the conditions that would make this pack appropriate, leaving agents to guess.
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.