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Net-Yield-After-Borrow Basis Signal

perps_basis_signal

Computes perp mark vs spot price across venues and surfaces actually-earnable yield. Funding-rate venues (HL, dYdX) generate real yield; pool perps (Jupiter, Adrena) flagged as not viable because they charge borrow on both sides. Returns per-venue trade + filtered opportunities + best trade.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetYesAsset to scan
min_yield_apr_pctNoMinimum net yield (APR %) for an opportunity to surface

TDQS

A4.2/5.0
Behavior4/5

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

Given no annotations, the description carries the full burden. It discloses that pool perps are flagged as not viable due to borrow on both sides, and that returns include per-venue trade, filtered opportunities, and best trade. This adds behavioral context beyond a simple computation description, though it doesn't cover edge cases like no opportunities.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the core function, followed by methodology detail and output structure. Every sentence contributes value, with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description summarizes the return structure (per-venue trade, filtered opportunities, best trade) and explains the filtering logic for venue viability. It lacks details on edge cases like no opportunities, but is adequate for a tool with only two parameters and a straightforward scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear parameter descriptions (asset, min_yield_apr_pct). The description adds context about filtering by yield and viability but does not provide additional syntactic detail beyond the schema. Baseline 3 is appropriate as the schema handles parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool computes perp mark vs spot price across venues and surfaces actually-earnable yield, with a specific output structure (per-venue trade, filtered opportunities, best trade). This distinguishes it from sibling tools like perps_cross_venue_funding by focusing on net yield after borrow and viability filtering.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context on venue types (funding-rate vs pool perps) which implies when this tool is relevant, but it does not explicitly state when to use it over alternatives or mention sibling tools. It gives clear context but no exclusions, so a score of 4 is appropriate.

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

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TDQS

A3.6/5.0
Disambiguation3/5

With 32 tools, several have overlapping purposes, such as wallet_history vs portfolio_history (both track wallet portfolio over time) and smart_money_flow vs smart_money_trenches (both follow smart money movements). However, most tools have clearly distinct scopes, and detailed descriptions help differentiate them.

Naming Consistency5/5

All tool names follow snake_case with a predictable verb_noun or noun phrase pattern (e.g., enrich_token, compare_wallets, perps_market_trend). The consistent structure makes the set easy to navigate, even the 'perps_' prefix group is uniform.

Tool Count2/5

32 tools is well above the 25-tool threshold, making the surface feel heavy. While the breadth reflects the wide domain of Solana analytics, the sheer number can overwhelm agents and increase the chance of selecting the wrong tool.

Completeness4/5

The tool set covers most aspects of Solana token/wallet/perp analysis, including enrichment, comparison, trend tracking, smart money flows, and perp market structure. Minor gaps exist, such as no direct historical OHLCV endpoint, but the existing tools handle core workflows well.