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Build Validation Pack

build_validation_pack

Return dry-run, QA, audit, and PASS criteria for one automation workflow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYes
riskNo
domainNo

Schema Changelog

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

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the tool 'returns' criteria, implying it is non-destructive and read-only, but does not confirm idempotency, side effects, or required permissions. This is minimal transparency for a tool that could potentially be involved in validation processes.

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

Conciseness3/5

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

The description is a single sentence with no extraneous content, which is concise. However, it is under-specified for a tool with three parameters and no other documentation. Front-loading is present but at the cost of completeness.

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

Completeness1/5

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

Given the tool's complexity (three parameters with no schema descriptions, no output schema, no annotations), the description is severely incomplete. It does not specify what the returned criteria look like, how parameters affect the output, or any usage context. This requires the agent to infer too much.

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

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has three parameters (goal, risk, domain) with 0% description coverage, and the tool description provides no explanation of how these parameters are used. The phrase 'for one automation workflow' hints at the goal parameter but does not clarify the role of risk and domain. The description fails to add any meaning beyond the schema's type constraints.

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 the resource as 'dry-run, QA, audit, and PASS criteria for one automation workflow.' This clearly indicates the tool's output and scope, distinguishing it from sibling tools like 'audit_automation_plan' which likely focuses on auditing rather than building validation packs. However, it lacks detail on what exactly 'PASS criteria' entails, preventing a perfect score.

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?

No explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites, conditions, or situations to avoid. A sentence like 'Use this when you need to generate validation criteria before running a workflow' would significantly improve the score.

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

B3.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: audit, intake, contract, validation, design, prompt generation, and recommendations. No two tools overlap in functionality, ensuring an agent can select the right tool without confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, with verbs like audit, build, design, generate, and recommend, and descriptive noun phrases. This uniformity makes the tool set predictable and easy to navigate.

Tool Count5/5

With 7 tools, the server covers the essential stages of automation design from intake to auditing without being sparse or overwhelming. The count is well-scoped for the domain.

Completeness5/5

The tool set covers the complete lifecycle of designing a no-shell automation: intake, design, validation, contract generation, prompt creation, and auditing. There are no obvious gaps in the workflow.