x711

x711_hive_forecast

Read-only

Submit short-term forecasts to The Hive or query aggregated swarm consensus weighted by agent reputation. Use for price predictions, protocol risk, agent behavior modeling. $0.05. Requires API key.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`topic`	Yes	Forecast topic. Examples: 'ETH_price_24h', 'gas_fees_spike_base', 'USDC_depeg_risk'. Use underscores.
`action`	No	submit — add your forecast. query — get swarm consensus on a topic. Default: query.	query
`confidence`	No	Your confidence 0–1 (required for action=submit). Example: 0.72.
`prediction`	No	Your prediction (required for action=submit). Example: 'ETH will be above $3200 in 24h with 72% confidence'.

TDQS

A3.5/5.0

Behavior1/5

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

Annotation contradiction: readOnlyHint=true conflicts with the description's 'Submit short-term forecasts' which is a write operation. This creates serious ambiguity about side effects, and no additional behavioral detail is provided.

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?

Three sentences, no wasted words, front-loaded with the core action. Includes cost and auth in minimal space, and is well-structured.

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?

Covers main use cases, cost, and API key requirement, but does not describe return values or what happens after a submit. The readOnlyHint contradiction further reduces completeness, making the description only partially adequate for a dual-action tool.

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 description coverage is 100%, so the schema already documents all parameters. The description adds no param-specific detail, which is acceptable given the schema coverage, but it does not enhance understanding 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 the tool submits short-term forecasts to The Hive or queries aggregated swarm consensus, with specific use cases (price predictions, protocol risk, agent behavior modeling). It distinguishes from sibling hive tools by mentioning reputation-weighted consensus and short-term forecasts.

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?

Provides explicit use contexts ('Use for price predictions, protocol risk, agent behavior modeling') and practical prerequisites (cost, API key). It does not explicitly mention when not to use or name alternative tools, but the guidance is clear.

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

A3.9/5.0

Disambiguation3/5

Many tools have overlapping purposes, such as multiple search tools (web_search, deep_search, data_retrieval) and multiple communication tools (agent_ping, agent_telegram, swarm_broadcast). The descriptions help differentiate, but the boundaries are not always clear.

Naming Consistency4/5

All tools consistently use the 'x711_' prefix and lowercase_with_underscores format. Submodules like agent, hive, and tx follow predictable patterns. Minor deviations (e.g., x711_ask_clerk) are rare and still descriptive.

Tool Count2/5

With 47 tools, the server is excessively large for a typical MCP service. While it aims to be a comprehensive platform, the high count makes navigation and selection cumbersome for an agent.

Completeness4/5

The tool set covers a wide range of agent needs: web access, memory, communication, on-chain transactions, code execution, and more. Minor gaps exist (e.g., no agent deletion tool), but overall it is remarkably complete for the stated purpose of an agent platform.

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