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recipes_secure_context_lineage_ledger

Return context lineage, reuse policy, stage requirements, hashes, and workflow envelopes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
decisionNo
stage_idNo
source_idNo
reuse_classNo
workflow_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
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. 'Return' implies a read operation, but the description does not explain how the optional parameters affect results, whether results are filtered or complete, whether there are access requirements, or how the ledger behaves with no parameters provided.

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 efficient sentence, front-loaded with the verb and resource. It is concise and not bloated, though the long list of return items makes it slightly dense and would benefit from a sentence that connects the return values to the optional parameters.

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?

The tool has no annotations and all five parameters are optional, so the description needs to explain selection semantics and parameter interactions; it does not. An output schema exists, so return-value shape is covered, but the core invocation context—what the ledger contains, how parameters narrow it, and what happens with no parameters—is missing.

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 explicitly map the five parameters (decision, stage_id, source_id, reuse_class, workflow_id) to the listed output categories. Some loose inference is possible—'reuse policy' to reuse_class and 'workflow envelopes' to workflow_id—but the agent is left to guess how each parameter filters or scopes the returned data.

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 clear verb ('Return') and enumerates specific resources: context lineage, reuse policy, stage requirements, hashes, and workflow envelopes. This meaningfully distinguishes the tool from the many recipe siblings, especially under the secure_context prefix, though it does not explicitly name what it is not or scope its input.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage: an agent would call this tool when it needs context lineage, reuse policy, stage requirements, hashes, or workflow envelopes. However, it gives no explicit guidance about when to prefer this tool over related tools, and it does not mention any exclusion or alternative.

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.