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

No annotations are provided, so the description carries the full behavioral burden. It states the tool returns a proof array, describes the daily Merkle root commitment, and discloses that only actively-priced products are included. The behavior is clear for a simple read-only proof fetch, though it does not describe error behavior or proof expiration.

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 longer than minimal, but it is well-structured with a clear opening, contextual 'WHY THIS MATTERS' section, and a note that highlights a critical limitation. Each section serves a purpose for an AI agent deciding whether this tool is appropriate.

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?

For a single-parameter tool with an output schema, this description is complete: it explains what the proof is for, how it is produced, how to use it, and the key edge case where proof generation is impossible. Nothing essential is missing for correct invocation and selection.

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?

The input schema already provides 100% coverage for product_id, so the baseline is 3. The description adds extra semantic value by explaining that the product must be actively priced (market_price > 0) to have a proof, which goes beyond the schema's generic 'TCGPlayer product ID' description.

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 opens with a specific verb and resource: 'Get a Merkle proof for on-chain price verification on LitecoinVM.' It further clarifies the deliverable as a proof array committed to the LitecoinVM blockchain by the oracle operator, making the tool's purpose unambiguous and distinct from a normal price lookup.

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 explains why an agent would want this tool instead of trusting regular API prices, which is strong contextual guidance. It also includes an explicit constraint: zero-price catalog entries cannot be proven. It does not name sibling alternatives like get_price or get_graded_proof, so it falls just short of full when-to-use versus alternative guidance.

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