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

With no annotations at all, the description carries the full behavioral burden; it does disclose the shape of what comes back (perps where funding and crowd bias agree, plus the funding-collecting side), which implies a read-only analytical output. It says nothing about data freshness, update cadence, latency, or coverage limits, which matter for a cross-source signal tool.

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 tight sentences: the first front-loads the data sources and the filter logic, the second front-loads the intended use cases. No filler and nothing buried.

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 is the only disclosure layer, and it does explain the returned fields well enough to interpret results. It is missing operational context (read-only status, freshness, any limits) that would make it fully self-sufficient.

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 no parameter meaning to add and the baseline of 4 applies. The description correctly implies no inputs are needed, since it describes only the returned set.

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 names a precise verb+resource: it crosses Hyperliquid perpetual funding rates with Reddit sentiment and returns perps where the two signals agree, along with which side collects funding. That is specific enough to distinguish it from siblings like akari_reddit_sentiment and akari_hl_market, which each cover only one input.

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 states the situations it serves — funding-rate arbitrage ideas, funding harvest signals, and perp carry trades — which gives an agent clear context for reaching for it. It stops short of naming alternatives or exclusions, so an agent must infer that single-source sentiment or market queries belong to the sibling tools.

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