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recipes_agent_trust_fabric_pack

Return Agent Trust Fabric dimensions, workflow tiers, source evidence, and buyer proof.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNo
trust_tierNo
workflow_idNo
dimension_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations supplied, the description carries the behavioral transparency burden. 'Return' implies a read-only retrieval operation and the description lists what it returns, which is helpful. However, it does not disclose how filtering parameters affect results, the scope of evidence, or any limitations, so the transparency is only partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no redundant phrasing. It names the verb and the key output categories efficiently, though it is terse to the point of omitting useful guidance in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with four optional parameters, no annotations, and no parameter explanations, this one-sentence description is incomplete. The output schema may document return shapes, but the agent still lacks enough context about filtering, parameter relationships, and when this recipe pack should be used among dozens of siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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 compensate by explaining any of the four parameters. The parameter names and the outputs listed in the description provide weak implicit mapping, but status, trust_tier, workflow_id, and dimension_id remain semantically vague with no enforcement, format, or meaning described.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Return') and identifies a clear resource ('Agent Trust Fabric'), then enumerates the main outputs: dimensions, workflow tiers, source evidence, and buyer proof. This makes the tool's purpose reasonably clear, though it does not explicitly differentiate it from sibling trust-related recipe packs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 alternatives such as recipes_secure_context_trust_pack, recipes_a2a_agent_card_trust_profile, or other trust-related packs. No context, exclusions, or preconditions are provided, leaving selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2.2/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count1/5

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.

Completeness4/5

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.