execution-run-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a write operation ('Execute', 'burning Shells'), involves costs based on model and tokens, and returns response content and cost. However, it misses details like rate limits, error handling, or authentication needs, which would enhance transparency.

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

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

The description is two sentences, front-loaded with the core purpose and followed by cost and return details. Every sentence earns its place by adding essential information without redundancy, making it efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (LLM execution with cost), no annotations, and no output schema, the description is fairly complete but has gaps. It covers purpose, cost mechanism, and return values, but lacks details on error cases, rate limits, or output format specifics. It compensates well but could be more comprehensive for a mutation tool.

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

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

Schema description coverage is 100%, so the schema already documents all parameters (model, messages, temperature, maxTokens). The description adds marginal value by mentioning cost calculation based on model and token usage, but does not provide additional syntax or format details beyond what the schema specifies. Baseline 3 is appropriate as the schema handles most documentation.

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

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

The description clearly states the specific action ('Execute an LLM request'), the resource involved ('by burning Shells'), and the outcome ('Returns the LLM response content and the cost in Shells'). It distinguishes this tool from sibling tools like get_balance or transfer by focusing on LLM execution with a cost mechanism, not financial queries or transactions.

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

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

The description implies usage for LLM requests with cost considerations, but does not explicitly state when to use this tool versus alternatives (e.g., if other tools handle LLM tasks differently) or provide exclusions. It offers some context but lacks explicit guidance on alternatives or specific scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.