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

With no annotations, the description carries the full behavioral burden. It usefully signals the tool is public (no auth implied), but omits defaults for the optional days/top_n window, pagination, and result ordering. For an unannotated tool this is a significant gap.

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 with the core purpose front-loaded and the filter note second. No filler, though the brevity comes at the cost of detail rather than being purely efficient.

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 annotations, no output schema, and 0% parameter coverage, the description is too thin for a three-parameter tool. It never defines LQF, ranking basis, or default window size, leaving the agent to guess at call semantics.

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 must compensate for all three parameters. It covers market_id as a filter and gestures at days via 'rolling window', but top_n is never mentioned and no defaults, units, or bounds are conveyed. Partial compensation only.

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 specific resource and scope: a public leaderboard of top LQF stipend earners over a rolling window. This distinguishes it from siblings like mm_stipend_estimate and mm_stipend_history by framing it as a ranked public listing, though it never names those alternatives. An agent can identify the operation, but 'LQF' is unexplained jargon.

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?

There is no statement of when to use this versus the nearby mm_stipend_estimate / mm_stipend_history tools, nor any prerequisites or exclusions. 'Optional market_id filter' hints at a filtering use case but gives no guidance on choosing it.

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