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flipr_opportunity_unsubscribe

Remove an opportunity webhook subscription. FREE — rate-limited only. [pricing: {"cost":"0","currency":"FREE","type":"free","network":"eip155:8453"}]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subscriptionIdYesThe subscription ID to remove

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full burden and only says 'Remove' and 'FREE — rate-limited only'. It does not disclose side effects, reversibility, authentication needs, or what happens after removal.

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 core description is a single concise sentence, front-loaded with the action. The embedded pricing tag adds some non-essential detail but does not significantly hinder clarity.

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

Completeness3/5

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

For a simple one-parameter tool, the description provides the basic purpose, but lacks information about return values, error conditions, or side effects, especially since there is no output schema or annotations.

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?

The schema fully describes the sole parameter subscriptionId, so the baseline is 3. The tool description adds no additional meaning about the parameter beyond the schema.

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?

Description clearly states 'Remove an opportunity webhook subscription' with a specific verb and resource, making it easy to understand and distinguish from the sibling tool flipr_opportunity_subscribe.

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?

No guidance is provided on when to use this tool versus alternatives. The description only states the action and includes pricing/rate-limit info, but does not mention related tools or scenarios.

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

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct aspect of the Flipr ecosystem: game info, health/status, flipping action, pot/opportunity monitoring, agent stats, referral program, and withdrawal. No two tools have overlapping purposes; even similar-sounding ones like flipr_opportunity and flipr_pot are clearly differentiated by ROI analysis.

Naming Consistency5/5

All tool names follow a consistent 'flipr_<noun>' snake_case pattern (e.g., flipr_agent_stats, flipr_flip). The naming is predictable and intuitive, making it easy for an agent to understand the hierarchy of operations.

Tool Count5/5

With 18 tools, the server covers the full scope of a betting game with referral features. Each tool serves a clear role without bloat. The count feels well-scoped for the domain, neither too sparse nor overwhelming.

Completeness4/5

The tool surface covers core gameplay (flip, health, game info), opportunity analysis (pot, opportunity, history, subscription), agent/referral management, and payout. A minor gap is the lack of a tool to retrieve an agent's own flip history beyond aggregated stats, but this does not hinder primary use cases.

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