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sanhao-global-experts

inlaw-tension-fix

Turn expertise into output. This inlaw tension fix prompt pack helps restaurant and brand teams produce professional results in minutes. Includes the complete prompt, usage guide, and edge-case handling.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.2/5.0
Behavior2/5

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

No annotations exist, so the description bears full behavioral burden, yet it never states side effects, permissions, cost, or output format. The single useful disclosure is that the pack "includes the complete prompt, usage guide, and edge-case handling," which hints at return structure but is framed as a product advertisement rather than operational behavior.

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

Conciseness2/5

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

It is short, but the opening sentence ("Turn expertise into output") and the "in minutes" claim are pure marketing that convey no operational information. The genuinely useful content — that it is a prompt pack with guide and edge cases — is buried after the fluff.

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?

With no annotations, no output schema, and an opaque name, the description carries the entire burden and fails: it does not explain what invoking returns, what topic the pack actually addresses, or how the `query` affects output. An agent could not confidently select or invoke this tool from the definition alone.

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

Parameters3/5

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

The schema fully documents the single optional `query` parameter ("Optional user query to scope the analysis"), so the 100% coverage baseline of 3 applies. The description adds no further meaning about how `query` shapes results, so it neither compensates nor detracts.

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

Purpose2/5

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

The name suggests a family/in-law conflict topic, but the description claims it serves "restaurant and brand teams" — an unexplained mismatch that leaves the actual resource ambiguous. "Turn expertise into output" and "produce professional results" are marketing generalities rather than a specific verb+resource statement, so an agent cannot reliably tell this apart from the hundreds of sibling prompt-pack tools.

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 when-to-use, when-not-to-use, or alternative is named, despite the presence of closely related siblings. The only contextual hint is an implied audience ("restaurant and brand teams"), which is insufficient to decide between this tool and the many adjacent prompt-pack tools.

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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