Return generated agentic app launch-review profiles and decisions.
| Name | Required | Description | Default |
|---|---|---|---|
| app_id | No | ||
| decision | No | ||
| risk_tier | No | ||
| buyer_stage | No | ||
| minimum_score | 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 disclosing behavior. It only says 'Return generated...' which gives no indication of side effects, prerequisites, data mutation, or any other operational characteristic. The agent has no sense of what happens when calling this tool.
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 sentence, which is concise but far too under-specified for a tool with five parameters and no schema hints. It is not appropriately sized; it fails to deliver necessary information rather than being efficiently structured.
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 tool's complexity (5 optional parameters, no schema descriptions, no annotations, and a non-trivial output), the description is woefully incomplete. An agent cannot understand the tool's inputs, outputs, or purpose well enough to invoke it correctly.
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 has zero description coverage, so the description must explain the five parameters (app_id, decision, risk_tier, buyer_stage, minimum_score). It does not mention any of them, leaving agents unable to determine valid values, formats, or relationships between inputs.
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 verb ('Return') and a resource ('generated agentic app launch-review profiles and decisions'), which is specific enough to avoid being a tautology. However, it does not explain what an 'agentic app launch-review' entails or how this pack differs from the many sibling packs (e.g., risk_scoring_pack, approval_receipt_pack). The purpose is partially clear but under-specified.
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 numerous sibling tools. No context, prerequisites, or exclusions are mentioned, leaving the agent to guess the intended scenario.
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.