Get information about Subnets/L1s on the P-Chain
| Name | Required | Description | Default |
|---|---|---|---|
| ids | No | Optional list of Subnet IDs to filter by | |
| limit | No | Max items to return (default: 50). Use with "offset" to page. | |
| offset | No | Number of items to skip from the start (default: 0). | |
| network | No | Avalanche network to query (default: mainnet) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. 'Get information' implies a read-only operation, which is useful, but it does not disclose return format, pagination behavior beyond the schema, or any other operational traits.
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 a single, front-loaded sentence with no redundant words. It communicates the core purpose efficiently.
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 simple read tool with well-documented parameters, the description is minimally adequate. However, with no output schema, it does not describe what information is returned, and it lacks usage alternatives, leaving some contextual gaps.
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?
Schema description coverage is 100%, and the schema already documents all parameters including defaults, enums, limits, and paging. The description adds no additional parameter meaning, so the baseline of 3 applies.
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 verb ('Get'), resource ('Subnets/L1s'), and scope ('on the P-Chain'). This distinguishes it from sibling tools like platform_get_blockchains and blockchain_lookup_subnet.
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 provided on when to use this tool versus alternatives such as blockchain_lookup_subnet or platform_get_blockchains. The description only states what the tool does, not when it should be preferred.
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 are redundant due to compatibility aliases (avalanche_docs_* vs docs_*, blockchain_get_* vs onchain_lookup) and overlapping functionality (chain_stats vs onchain_query, onchain_activity vs onchain_query ops, acp_list vs info_acps). Agents may struggle to select the correct tool when multiple appear to serve the same purpose, despite descriptions clarifying aliases.
Naming patterns are inconsistent: some tools use noun_verb (acp_list, docs_fetch), some use verb_noun (build_plan), and others use prefixes like platform_get_, info_get_, and onchain_. The mix of styles (snake_case, noun phrases, verb phrases) makes it hard to predict tool names.
With 48 tools, the count is high and inflated by compatibility aliases and granular platform_get_* wrappers. The scope spans multiple domains (docs, on-chain, platform API, ACPs, console), which could be better modularized. Many tools are trivial variants (e.g., platform_get_block vs platform_get_block_by_height) adding unnecessary bulk.
The server provides thorough read-only coverage for Avalanche: docs search, ACP management, on-chain lookups, indexed stats, platform API getters, and console flow guidance. While there is no transaction submission (likely intentional), the surface covers most queries a developer would need, with minor gaps like detailed token transfer history.
