cpi_meta
PRO. Dataset structure/metadata for the CPI query.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| access_token | No | Subscriber token from /success (or Authorization: Bearer) |
PRO. Dataset structure/metadata for the CPI query.
| Name | Required | Description | Default |
|---|---|---|---|
| access_token | No | Subscriber token from /success (or Authorization: Bearer) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden, and it discloses almost nothing: the "PRO" prefix implies a subscription gate but doesn't say what happens without one, and nothing states that this is a read-only operation or what the response looks like. The access_token field in the schema implies auth, but the description itself doesn't address it.
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?
Two short fragments with no filler, which is good, but the brevity comes at the cost of substance rather than being tight. "PRO." is front-loaded but unexplained, and the second fragment is the only content.
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?
There is no output schema and no annotations, so the description is the only source of information about what this tool returns — yet it never explains which metadata (series list, dimensions, units, frequency) an agent would get back. For a metadata/discovery tool, that omission leaves the agent unable to decide whether calling it is worthwhile.
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?
Only one parameter exists and schema description coverage is 100%, so the access_token semantics are fully documented in the schema. The description adds nothing beyond that, which is the expected baseline when the schema does the work.
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?
"Dataset structure/metadata for the CPI query" identifies the resource domain (CPI metadata) and implies this is the schema/structure companion to the data-returning siblings like cpi_history and latest_cpi. However, there is no verb and no explicit statement of what metadata is exposed, so the agent must infer the purpose from the tool name and sibling set rather than reading it directly.
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?
No guidance on when to call this versus cpi_history, cpi_group, or latest_cpi. The only usage-relevant signal is the leading "PRO", which hints at a paid-tier prerequisite but is never explained. No prerequisites, no exclusions, no alternatives named.
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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