Return the Agentic System BOM for workflows, agents, identities, MCP tools, and evidence.
| Name | Required | Description | Default |
|---|---|---|---|
| namespace | No | ||
| agent_class | No | ||
| workflow_id | No | ||
| component_type | 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?
The description only says the tool 'returns' the BOM, which implies a read operation but discloses no further behavioral traits. With no annotations, the description carries the full transparency burden and does not address whether the BOM is computed on demand, how filters affect output, or whether side effects or prerequisites exist.
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 front-loaded sentence with no filler, repetition, or unnecessary detail. Every word contributes to communicating the core deliverable and its scope.
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 having an output schema, the tool has no annotations, no parameter descriptions, and no usage guidance. The agent cannot determine how to construct meaningful filter values or what namespace or component_type mean, so the invocation context is materially incomplete.
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 namespace, agent_class, workflow_id, or component_type. The listed BOM categories only weakly hint at workflow_id and agent_class, providing no information about value formats, allowed values, or how parameters interact.
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 an active verb and names a specific deliverable, 'Agentic System BOM,' then enumerates covered categories: workflows, agents, identities, MCP tools, and evidence. This distinguishes it from recipe/pack siblings and gives the agent a concrete sense of what the tool returns.
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?
No guidance is provided about when to use this tool versus alternatives such as recipes_agentic_readiness_scorecard or recipes_agentic_incident_response_pack. There are no conditions, exclusions, or references to sibling tools, leaving selection entirely to inference from the name.
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.