Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are supplied, so the description carries the full disclosure burden. It usefully explains the meaning of the disagreement_pct output and the >1% threshold that signals arbitrage or source discrepancy, but says nothing about scope (which signals are scanned), ordering, or whether grouping can be empty — meaningful gaps for a tool with no structured hints.

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 sentences with no filler: the first defines the behavior and gives a grounding example, the second explains the key metric's interpretation. Front-loaded and every clause earns its place.

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?

With no parameters and no output schema, the description is the only source of information about what comes back. It explains the grouping concept and the disagreement_pct signal but does not say what a group actually contains (signal identifiers, members, ordering), leaving the return shape partially opaque for a caller trying to use results.

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 tool takes zero parameters, so there is nothing for the schema to document and no parameter semantics to add. The description instead spends its words on interpreting output, which is the appropriate use of space here; baseline 4 applies.

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 gives a concrete verb ('Find') and a specific resource ('groups of active signals measuring the same metric'), plus a clarifying example (BTC price across exchanges). It implicitly contrasts with list_active_signals by returning groups rather than a flat list, but never names that sibling, so the differentiation is inferable rather than explicit.

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?

Usage is only implied: the arbitration/data-source-discrepancy framing hints at when this is valuable, but there is no explicit statement of when to call this versus list_active_signals or verify_snapshot, and no prerequisites or exclusions. An agent can guess the intent but must infer the routing decision.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.