Offers 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 adds meaningful context by stating that every report is 'read and improves matching and trust scoring,' indicating a persistent, side-effectful action. It doesn't mention authentication or irreversibility, but for a feedback submission tool this is reasonable.

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 purpose, and contains no redundant or filler words. Each clause earns its place: one for action, one for timing/impact.

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 simple feedback tool with 3 params and no output schema, the description covers the essential context: what it does, when to use it, and its effect on the system. It could mention what the response looks like, but that's not required given the absence of an output schema and the tool's simplicity.

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 params already have descriptions. The tool description adds value by clarifying the intent behind verdicts (e.g., 'wrong, misleading' maps to bad, 'notably good' to good) and providing concrete user reactions ('wrong product, bad price, broken link, great find') that help the agent populate the 'note' and 'verdict' fields.

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 tool's purpose: 'Report that a search_offers result was wrong, misleading, or notably good.' It uses a specific verb ('report'), a clear resource ('search_offers result'), and distinguishes itself from its sibling tool search_offers by focusing on feedback rather than retrieval.

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 gives explicit timing: 'Use after the user reacts to a result.' It also explains the consequence ('Every report is read and improves matching and trust scoring'), which reinforces appropriate use. While it doesn't explicitly state when NOT to use the tool, the guidance is clear enough given the single sibling tool.

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

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

With no annotations provided, the description carries the behavioral disclosure burden. It adequately reveals that offers are live and normalized, includes delivery estimates, and returns computed best/fastest trusted offers. It does not mention rate limits or auth, but for a read-only search tool this is acceptable. Slight deduction for not stating whether results are cached or if any side effects occur, though none are expected.

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 concise relative to the amount of useful content it packs: purpose, usage guidance, input format, and output fields. It is front-loaded with the key differentiator ('live, normalized purchase offers'). The 'Returns...' sentence is informative but a bit dense; still, each sentence earns its place.

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 simplicity (2 parameters, no output schema), the description provides a complete picture: what the tool does, when to use it, what inputs are accepted, and what fields will be returned. No critical information is missing.

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%, and both parameters are well documented in the schema. The description's mention of 'free text or GTIN/UPC/EAN' and 'optional US zip code' largely restates schema information, adding minimal new meaning. Baseline 3 is appropriate.

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 uses a specific verb ('Find') and resource ('live, normalized purchase offers for a specific product across merchants'), clearly distinguishing from generic web search and the sibling tool 'report_feedback'. The scope is unambiguous.

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?

Explicitly states when to use the tool ('whenever the user asks about product prices, deals, whether a price is good, where to buy something, delivery times...') and when NOT to use it ('NOT generic web search'). This is exactly the guidance needed for an agent to select the right tool.

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