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sanhao-global-experts

resume-polish-pro

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use resume polish pro workflow - no prompt engineering needed. Ships as a full prompt kit with step-by-step instructions and a 30-day support promise.

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?

With no annotations, the description carries the full behavioral burden, yet it never says what invoking the tool does, what it returns, or whether it mutates anything. 'Ships as a full prompt kit with step-by-step instructions' is a vague hint about output form but is not a usable behavioral contract, and the support promise is commercial boilerplate.

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?

Three sentences, and the lead sentence is both off-topic (restaurant & brand intelligence) and misleading, while the closing sentence is a support promise rather than tool information. The structure is front-loaded with the least useful content.

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?

There is no output schema and no annotations, so the description needed to explain the deliverable and its behavior. Instead it leaves an agent with marketing phrases, no return-value expectation, and no differentiation from the large resume tool family.

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?

Schema description coverage is 100% for the single optional 'query' parameter, so the baseline is 3. The description adds no meaning about how the query scopes the analysis, but the schema already documents it adequately.

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 description opens by calling itself an 'AI-powered restaurant & brand intelligence pack,' which has nothing to do with the tool name resume-polish-pro, and then only restates the name as 'a ready-to-use resume polish pro workflow.' An agent cannot tell from this text what the tool actually produces or how it differs from resume-polish-tool, resume-optimizer-pro, or resume-rewrite-tool in the sibling list.

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 statement of when to use this tool versus the many resume siblings, no prerequisites, and no exclusions. The only guidance-like sentences ('no prompt engineering needed,' '30-day support promise') are sales copy that does not help an agent decide between alternatives.

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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