Skip to main content
Glama

rh_spread

Effective round-trip execution cost for a tokenized stock right now: best executable buy vs best executable sell price for a small reference clip across all venues, and the resulting effective spread %, modeled with pool fee + constant-product impact. Send { ticker, clipUsd?, feePct? }. The cost-to-trade snapshot for execution agents. [x402 paid tool — price $0.005; POST /api/rh/spread]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
feePctNoAssumed pool swap fee %, default 0.3
tickerYesStock/ETF ticker
clipUsdNoReference clip size in USD, default 500

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the modeling approach (pool fee + constant-product impact) and the small-reference-clip assumption, indicating non-destructive read-only behavior. It also notes the tool is paid ($0.005). It does not mention authentication or rate limits, but for a read-only info tool this is acceptable.

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

Conciseness4/5

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

The description is three sentences covering purpose, parameters, and pricing/endpoint in a front-loaded manner. It is concise with no redundancy, though the pricing and endpoint info could be separated. Each sentence adds value.

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?

The description explains the output (best buy/sell prices and effective spread %), the modeling assumptions, and the small-clip context. No output schema exists, but the return values are adequately described. Minor lack of explicit output type, but sufficient for understanding.

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 descriptions for ticker, clipUsd, and feePct. The description repeats the parameter list but adds no new semantic detail beyond what the schema provides. A baseline 3 is appropriate as the schema already fulfills parameter documentation.

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 the effective round-trip execution cost (spread) for a tokenized stock, specifying the verb 'snapshot' and the resource 'execution cost'. It distinguishes from siblings like rh_depth (market depth) and rh_premium (premium/discount) by focusing on modeled cost with pool fee and constant-product impact.

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?

It implies usage by 'cost-to-trade snapshot for execution agents' and lists the needed parameters {ticker, clipUsd?, feePct?}. However, it does not explicitly state when NOT to use it (e.g., large orders) or provide alternative tools. The context is clear but lacks explicit exclusions.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation4/5

Tools are organized by domain prefix (e.g., 'crypto_', 'rh_', 'snipe_'), which helps distinguish between areas. Within each domain, they serve distinct purposes, though some overlap between domains exists (e.g., price data appears in multiple groups). Overall, an agent can navigate effectively.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with a domain prefix and a verb_noun combination (e.g., 'compliance_risk', 'rh_stock', 'snipe_honeypot'). This makes the API predictable and easy to explore.

Tool Count2/5

With 159 tools, the server is extremely large. While the broad scope of web3 and utility functions justifies many tools, the count is significantly above the typical range for a coherent toolkit, potentially overwhelming agents and increasing selection error.

Completeness4/5

The toolkit covers a wide range of web3 operations: crypto, DeFi, compliance, safety, scheduling, memory, etc. There are no obvious major gaps for its intended purpose, though some niche areas might be missing.