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

With no annotations, the description carries the full burden and does substantial work: it discloses that costs are computed as a real round-trip (Jupiter quote both directions + Phoenix order-book walk + fees), that breakeven days are derived, and that after-hours/earnings flags matter. It implies a read-only analysis but never states side-effect profile, latency, or data freshness, which is the residual gap for an unannotated 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?

The core action is front-loaded and the return inventory is packed into a single sentence without filler. The parenthetical load and the trailing 'NFA' are slightly noisy, and the return list could be enumerated more scannably, but overall every sentence carries information.

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?

No output schema exists, so the description must describe returns itself — and it does, naming prices/gaps, funding APR, round-trip cost, breakeven days, flags, and the four verdict values. For a two-parameter analysis tool with a rich computed output, that is enough for an agent to call it and interpret the result.

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 100%, so the baseline of 3 applies; the enum and the 'Notional per leg' description already document both parameters. The description adds only marginal meaning, notably that size drives the cost and breakeven math ('the real round-trip cost at your size'), while its symbol list largely duplicates the enum.

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 first clause names the exact instrument pair and strategy: 'Tokenized-stock basis trade: long the xStock ... on Jupiter, short its Phoenix perp, collect funding.' An agent can immediately tell this is a basis/funding analytics tool rather than a screener or quote tool. It stops short of naming the neighboring perps_basis_signal or perps_cross_venue_funding to explain how it differs, so it is clear but not sibling-differentiated.

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?

Provides a concrete triggering question ('is the NVDA basis worth it at $10K?') that maps directly onto the two parameters, which is strong usage context. There are no explicit exclusions or named alternatives (e.g., when to prefer perps_basis_signal or stonk_quote instead), so it falls short of a full when/when-not treatment.

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