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sanhao-global-experts

homework-companion

Save hours every week. This homework companion toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.7/5.0
Behavior1/5

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

No annotations are supplied, so the description carries the full burden — and it discloses no behavior whatsoever: no indication of what the tool returns, whether it mutates anything, what permissions it needs, or what the playbook contains. Marketing claims like "battle-tested" and "save hours" are not behavioral disclosure.

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 sentences are sales copy rather than specification — "Save hours every week" and "No setup" occupy the front-loaded position that should describe what the tool does. The text is not padded, it is simply wasted on claims no agent can act on.

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?

No output schema, no annotations, and a description that contradicts the tool's own name leave an agent with no idea what calling it produces or whether it is even the right tool. For a tool offered alongside hundreds of near-name-colliding siblings, this is materially incomplete.

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?

There is a single optional parameter, and the schema already documents it at 100% coverage ("Optional user query to scope the analysis"). The description adds nothing about how a query changes the output, but with full schema coverage the baseline of 3 applies.

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?

"homework-companion" implies help with schoolwork, but the description describes a "prompt and operating playbook for restaurant/brand growth" — a different domain entirely. It names a resource (prompt + playbook) but no concrete operation, and an agent cannot reconcile the name with the stated purpose.

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

Usage Guidelines1/5

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

No when-to-use guidance at all. With siblings like brand-fnb-playbook, restaurant-ops-diagnostic, and k12-homework-system already present, the description offers nothing to route an agent between them. "Works in any LLM chatbot" is not selection criteria.

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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