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sanhao-global-experts

cs-soothing-agent

Save hours every week. This soothing agent 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 behavioral burden and delivers none of it. 'Works in any LLM chatbot' and 'no setup' describe packaging, not behavior — nothing about what the call returns, whether it mutates state, how the playbook is scoped, or any limits.

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 short sentences, but every one is promotional filler ('Save hours every week,' 'battle-tested,' 'No setup'). Nothing is front-loaded about the tool's function, so the space is wasted rather than efficient.

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?

With no annotations, no output schema, and only a vague 'toolkit' framing, the description leaves the agent unable to predict the return value, the invocation pattern, or the domain boundary. For a tool whose entire value is an unspecified 'playbook,' this is inadequate.

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 coverage is 100% for the single optional 'query' parameter, so the schema itself already documents its meaning and baseline 3 applies. The description adds nothing about how the query scopes the analysis, and 'no setup' actually implies input is unnecessary, which is mild noise rather than clarification.

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 only says it is a 'soothing agent toolkit' with a 'prompt and operating playbook' for 'restaurant/brand growth.' That is marketing positioning rather than a verb+resource statement, so the agent cannot tell what the tool actually produces or how it differs from near-identical siblings like brand-fnb-playbook, restaurant-ops-diagnostic, or chain-restaurant-war-room.

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?

There is no when-to-use guidance at all: no triggers, no prerequisites, no exclusions, and no named alternative. In a catalog with hundreds of overlapping brand/F&B tools, the absence of any routing guidance makes selection guesswork.

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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