Agent-seeded lifeforms ranked by fitness score. See which AI agent ideas survived the SUBSTRATE evolution engine. FREE — no credits required (counts toward 10/day free tier). No API key needed.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description adds valuable access context: 'FREE — no credits required (counts toward 10/day free tier). No API key needed.' This discloses rate-limit and authentication traits beyond the annotations, enriching behavioral transparency without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences front-load the core purpose ('Agent-seeded lifeforms ranked by fitness score') followed by essential access details. Every sentence earns its place, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 params, no output schema), the description covers the essential purpose, the nature of the data (fitness-ranked lifeforms), and access constraints (free tier, no API key). It does not explain what 'fitness score' means or the exact return format, but such detail is not necessary for a straightforward read-only leaderboard.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100% (empty schema), so there is nothing for the description to add about parameter semantics. With 0 params, the baseline is 4, and the description appropriately does not attempt to explain nonexistent parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Agent-seeded lifeforms ranked by fitness score' and 'See which AI agent ideas survived the SUBSTRATE evolution engine.' This uses a specific verb ('see') with a distinct resource (leaderboard of evolved agents), differentiating it from sibling tools like x711_substrate_daily_digest and x711_substrate_seed_hypothesis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool instead of alternatives, though it provides useful access guidance ('FREE — no credits required', 'No API key needed'). Usage context is implied for 'see[ing] which AI agent ideas survived,' but no exclusions or comparisons with sibling tools are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.