get_leading_indicatorsWhich social and on-chain signals have historically MOVED FIRST for an asset.
This is the lead/lag question that get_correlation deliberately does not
answer. A lead measured over a past window is not a forecast and the
response does not present it as one — it is the observed ordering of two
series, and it can break.| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: the response is an observed ordering of two series, not a forecast, and it can break. This goes beyond the annotations and helps set expectations about the output's meaning and limitations.
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 compact and front-loaded: the first sentence states the core purpose, and the second adds the critical caveat and sibling distinction. Every sentence earns its place, and there is no redundant repetition of the title or schema.
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 single-parameter read-only tool with rich annotations, the description is nearly complete. It explains what the tool does, what it does not do, and the key limitation of the output. The only minor gap is that it does not explicitly state the expected format of the 'symbol' parameter, but the schema and the tool's name make this inferable.
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%, so the description carries the burden for parameter meaning. The description implies the tool operates on an asset ('for an asset'), which maps to the required 'symbol' parameter, but it does not explicitly state that 'symbol' is the asset identifier or provide format details. With only one required parameter and a clear implication, a 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 states a specific verb ('get') and resource ('leading indicators'), and immediately clarifies the scope: social and on-chain signals that have historically moved first for an asset. It also explicitly distinguishes itself from get_correlation, which helps an agent differentiate between the two tools without opening schemas.
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 names get_correlation as the sibling that does not answer the lead/lag question, and clarifies that this tool is the one that does. It also warns that a lead measured over a past window is not a forecast, which is a clear usage caveat. This is strong when-to-use guidance.
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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