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github_sanhaoyoung_sanhao_global_experts_procrastination_breaker_procra

Turn expertise into output. This procrastination breaker prompt pack helps restaurant and brand teams produce professional results in minutes. Includes the complete prompt, usage guide, and edge-case handling. Paid expert skill · 0.01 USDC per call via x402 on Base (USDC contract 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913). A2A endpoint: https://sanhaoyoung821208-d5dv139af0958c.service.tcloudbase.com/a2a Agent card: https://www.a2a-registry.org/agents/7b10730c-d423-416d-b74a-a73385957920

Input Schema

NameRequiredDescriptionDefault
queryYesYour request to the "Procrastination Breaker" expert.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden, and it does disclose important behavior: this is a paid call at 0.01 USDC via x402 on Base, with the USDC contract address and A2A/agent-card endpoints given. However, it says nothing about what invoking the tool actually returns, latency, or error/payment-failure behavior, so the safety and outcome profile remains incomplete.

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 text is short but split between a marketing tagline and payment/endpoint plumbing. The sentence "Includes the complete prompt, usage guide, and edge-case handling" is ambiguous — it is unclear whether those are returned by the tool or are documentation for the caller — which adds noise rather than clarity.

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 single-query expert endpoint with no output schema and no annotations, the description should make clear what an invocation yields. Instead it mixes 'prompt pack' (a static artifact) with 'produce professional results' (generation), leaving the return contract ambiguous, and it never states whether the call is read-only or how the paid invocation is authenticated.

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 required `query` parameter, so the schema already documents its purpose. The description adds no syntax, formatting, or content guidance for constructing the query beyond the schema's own text; baseline 3 applies.

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

Purpose3/5

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

The description leads with marketing copy ("Turn expertise into output") and only loosely identifies the resource as a "procrastination breaker prompt pack" for restaurant and brand teams. An agent can guess it is a free-form expert-skill endpoint, but the actual capability — what the expert produces — is never stated concretely, and nothing distinguishes it from the hundreds of similarly named sibling skills.

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 when-to-use guidance, no when-not-to-use, and no comparison to alternatives among the siblings. The only actionable context is the payment requirement (0.01 USDC per call), which tells the agent about cost but not about when this skill should be selected over another.

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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