Individual reclaim opportunities with evidence — what to claim from Amazon and why. Call after get_reconciliation_summary to list the actual claims. status: open, dismissed, filed or all. Requires a connected Amazon account (closed beta).
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| status | No | open | |
| claim_type | No | all |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully convey behavioral traits. It discloses that the tool is a read operation (listing claims) and mentions the prerequisite. However, it does not describe pagination behavior (despite page/limit parameters), output structure, rate limits, or data freshness, leaving some gaps.
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, consisting of three sentences that front-load the core purpose, then provide usage ordering and parameter hints. No extraneous information is included; every sentence adds value.
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 has 4 parameters, no output schema, and no annotations, the description covers the essential purpose, when to call, and a prerequisite. However, it lacks details on claim_type values, pagination behavior, output format, and error handling, which would be beneficial for a complete understanding.
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 has 0% coverage (no parameter descriptions). The description adds meaning for the 'status' parameter by listing possible values: 'open, dismissed, filed or all.' However, it does not explain the 'claim_type' parameter or provide details for 'page' and 'limit' beyond their schema defaults. Thus, it partially compensates but not fully.
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 returns 'Individual reclaim opportunities with evidence — what to claim from Amazon and why.' It uses a specific verb ('get') and resource ('reconciliation claims'), and distinguishes itself from the sibling tool 'get_reconciliation_summary' by indicating it lists actual claims rather than a summary.
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 explicitly advises calling this tool 'after get_reconciliation_summary to list the actual claims,' providing clear sequencing guidance. It also mentions the prerequisite 'Requires a connected Amazon account (closed beta)' and lists valid status values, though it does not explicitly state when not to use it or compare to other similar sibling tools.
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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Each tool targets a distinct data type or action (e.g., product analysis, deal types, FBA operations). Even similar-sounding tools like get_deal_results and get_oa_deals are clearly separated by domain (A2A vs OA) in descriptions. No significant overlap.
All tools follow a clear verb_noun pattern with underscores (e.g., analyse_product, create_deal_task, get_credits). The consistent 'get_' prefix for retrieval tools and varied but predictable action verbs make the set easy to navigate.
At 37 tools, the set is large but covers a broad Amazon seller ecosystem (research, sourcing, FBA, deals, monitoring). Each tool serves a distinct purpose, and the count reflects the domain's complexity without being bloated.
The tool surface covers all major seller workflows: product analysis, profit calculation, sourcing, deal discovery, storefront monitoring, FBA operations, purchase tracking, price alerts, and reconciliation. No obvious gaps for core tasks.
