get_price_historyLegacy commerce tool. Retrieve retailer price observations and freshness; contains no clinical efficacy conclusion.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds value by labeling the tool as 'legacy' and clarifying the data scope (retailer price observations and freshness), which is useful context beyond the annotations.
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 long and front-loads the primary purpose. Every word adds value, with no redundancy or filler.
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 low complexity (one parameter, no output schema), the description adequately conveys what data is returned (price observations and freshness) and sets expectations about its legacy and non-clinical nature. It could include more detail about response structure, but is sufficient for this simple 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 0%, and the description does not mention the 'product_id' parameter at all. The parameter name is self-explanatory, but the description fails to provide any additional meaning or format details, leaving a gap that should be compensated.
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 it is a legacy commerce tool that retrieves retailer price observations and freshness, and explicitly notes it contains no clinical efficacy conclusion. This distinguishes it from sibling evidence-based tools.
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?
It implies use for commerce price data and explicitly warns against using it for clinical efficacy conclusions, which serves as a usage boundary. However, it does not name alternative tools or state explicit 'when to use' versus 'when not to use' instructions.
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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The evidence tools (compare_evidence, get_citations, get_evidence_summary, query_evidence_map, search_evidence) and commerce tools (compare_supplements, get_price_history, get_product, recommend_for_goal, search_supplements) are clearly separated, but a few pairs like compare_evidence vs compare_supplements and search_evidence vs query_evidence_map could cause confusion despite different data sources being described.
All tool names follow a consistent verb_noun snake_case pattern (e.g., search_evidence, get_citations, compare_evidence), making it easy to predict functionality from the name.
The 10 tools are within a reasonable range, but the legacy commerce tools (compare_supplements, get_price_history, get_product, recommend_for_goal, search_supplements) add redundancy and could be trimmed without losing core functionality, making the set slightly over-sized.
The evidence surface fully covers search, summary, comparison, citation retrieval, and dataset querying, while the commerce tools provide complete product lookup, price history, and recommendation capabilities. No major gaps are apparent for the stated purpose.