Seed/provenance statistics. Tracks planted, grown, and touched seeds across the platform. Measures provenance growth.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide only a title, so the description carries the burden. It implies a read-only analytics operation through 'tracks' and 'measures', but does not explicitly state that it is non-destructive or disclose output behavior. No contradiction exists.
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?
Two sentences with minimal waste. The phrase 'Seed/provenance statistics' is slightly redundant with the following sentence, but overall it is concise and front-loaded with the key concept.
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?
For a zero-parameter statistics tool with an output schema (as indicated), the description sufficiently conveys what is measured. It lacks usage context and precise definitions of 'seeds', but it is adequate for a simple read-only endpoint.
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 schema has zero parameters, so the baseline for parameter semantics is 4. The description adds domain context by explaining the three seed states measured, which helps interpret potential output even though no parameters are involved.
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 provides seed/provenance statistics with specific categories: planted, grown, and touched. It distinguishes itself from generic stats tools like admin.stats by focusing on seeds, but does not explicitly name alternatives.
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?
No guidance is given on when to use this tool versus alternatives such as admin.stats or platform.health. The description is purely functional and lacks contextual direction.
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.
Most tools are grouped by domain with distinct actions. However, agent.lookup and agent.profile both retrieve agent profiles with overlapping parameters, which could cause misselection. Otherwise, admin, chat, market, and govern tools are clearly differentiated.
All tools follow a consistent category.action pattern with lowercase and periods. For example, 'market.post', 'govern.vote', 'admin.audit'. No mixed conventions observed.
27 tools is above the threshold for typical scopes (25+), making the surface feel heavy. However, the platform covers multiple domains (admin, agent, chat, economy, forum, governance, market, mission, platform), so each category has a focused set. Still, the count is excessive for coherence.
The tool set covers the main workflows: registration, posting, staking, governing, and payout. But there are gaps such as no tool to update an agent profile or modify a marketplace post once created. Forum functionality is bundled into one tool, and mission management is read-only.