report_feedbackReport that a search_offers result was wrong, misleading, or notably good. Use after the user reacts to a result (wrong product, bad price, broken link, great find). Every report is read and improves matching and trust scoring.
| Name | Required | Description | Default |
|---|---|---|---|
| note | No | What was wrong or right, briefly | |
| query | Yes | The original product query | |
| verdict | Yes | Overall judgment of the result |
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.
Add one secure layer between your agents and this server.
The two tools have completely distinct purposes: one searches for offers, the other reports feedback on search results. There is no overlap or ambiguity between them.
Both tool names follow the verb_noun pattern (search_offers, report_feedback) and use consistent snake_case formatting. The pattern is predictable and clear.
With only two tools, the server feels minimal. The narrow scope (searching and reporting feedback) means two tools can suffice, but it is still on the thin side compared to the typical 3-15 tool range.
The core workflow of searching for offers and providing feedback is covered. Minor gaps exist (e.g., no tool to fetch individual offer details or manage feedback), but agents can accomplish the primary purpose without dead ends.