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

No annotations are supplied, so the description carries the full burden and does add real context: price ($0.007), data provenance ('live market data' via APEX AI), and a 30-minute cache that tells the agent results may be stale within that window. It omits failure modes and whether the read is rate-limited, but the disclosed cost/cache/source traits are exactly what annotations would otherwise carry.

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?

Front-loads the price and the core purpose, then defines the output dimensions, then provenance and cache. Dense but all sentences carry information. The 'Powered by APEX AI analyzing live market data' sentence is slightly promotional but also conveys the data source.

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 output schema and no annotations, the description must describe both what comes back and operational traits, and it does: five named return fields plus cost and cache lifetime. Missing only edge-case behavior (what happens on data outage, whether the output is directional advice or raw metrics).

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 the baseline is 4 and there is nothing parameter-wise the description needs to compensate for. The enumerated output categories substitute usefully for the missing parameter semantics.

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?

States a specific resource and analysis type ('AI-powered market narrative analysis') and enumerates the five dimensions it returns: primary narrative, saturation level, alpha window, rotation signal, contrarian setup. An agent knows exactly what it gets. It does not distinguish itself from narrative-adjacent siblings like signal_intelligence or capital_rotation_signal, so it stops short of a 5.

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 implied by the subject matter (crypto market narrative/saturation assessment) but there is no explicit when-to-use, when-not-to-use, or named alternative. With zero parameters the invocation decision is simple, which limits the cost of the gap, but an agent comparing it against capital_rotation_signal or apex_pulse gets no routing help.

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