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therealjlc1

SharpEdge MCP Server

by therealjlc1

get_features

Retrieve the complete feature set of SharpEdge AI, including exclusive tools for sports betting analysis such as Ghost Mode, Dream Bet Builder, and Edge Replay.

Instructions

Get the full feature list of SharpEdge AI including 10 unique features no competitor offers: Ghost Mode, Dream Bet Builder, 4 Alert Modes, Edge Replay, Streak Alerts, Cashout Advisor, Hedge Calculator, Circuit Breakers, Confidence Grades, and Social Proof Win Cards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the tool retrieves a feature list and enumerates 10 specific features, but doesn't disclose behavioral traits such as whether it's a read-only operation, requires authentication, has rate limits, or what the return format looks like. For a tool with zero annotation coverage, this is insufficient.

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

Conciseness3/5

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

The description is a single sentence that states the purpose and lists features. It's front-loaded with the core action but includes an exhaustive feature list that may be verbose for an AI agent. The listing of 10 features adds detail but could be considered extraneous if the schema or output handled this.

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

Completeness2/5

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

Given no annotations and no output schema, the description should provide more context about what the tool returns and its behavior. It lists features but doesn't explain the return structure, format, or any operational constraints. For a tool with rich potential output (feature list), this is incomplete.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here. Baseline is 4 for zero parameters, as no compensation is needed.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Get the full feature list of SharpEdge AI' with a specific verb ('Get') and resource ('feature list'). It distinguishes itself from siblings by focusing on features rather than betting explanations, live stats, pricing, or sample edges. However, it doesn't explicitly contrast with sibling tools in the description text itself.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for usage, or comparisons with sibling tools like get_pricing or get_sample_edges. The agent must infer usage based on the purpose alone.

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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