Get the validators and their weights of a Subnet/L1 at a given P-Chain height
| Name | Required | Description | Default |
|---|---|---|---|
| height | Yes | The P-Chain height to query validators at, or "proposed" | |
| network | No | Avalanche network to query (default: mainnet) | |
| subnetID | No | The Subnet ID to query validators for (default: Primary Network) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavior. It clearly indicates a read-only GET operation. It does not mention return format, pagination, error conditions, or any side effects, but for a simple get, it is adequately transparent. The absence of output schema makes the description's mention of 'weights' somewhat vague, but it does not hide destructive actions.
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 sentence, front-loaded with the action and scope. There is zero fluff or redundancy. Every word contributes to the core message. This is an exemplary concise description.
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 schema covers all parameters, and the tool is a simple read operation, the description is largely sufficient. However, it doesn't specify what the response contains (e.g., a list of validators with their weights) or any constraints like 'height must be <= current height'. While not critical, adding a note about the output format would improve completeness.
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 input schema has 100% coverage for all three parameters: height, network, and subnetID. The description adds no additional meaning beyond what the schema already provides. It merely reiterates the height concept and doesn't clarify defaults (e.g., mainnet) or parameter interactions. Baseline of 3 applies due to full schema coverage.
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 purpose: retrieving validators and their weights at a specific P-Chain height. The verb 'get' plus the specific resource ('validators and their weights') and scope ('of a Subnet/L1') make the function unambiguous. It distinguishes from sibling tools like platform_get_current_validators by the explicit 'at a given P-Chain height' phrase, even though it doesn't name them.
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 implies usage for historical queries by mentioning 'at a given P-Chain height', but it does not explicitly state when to use this tool versus alternatives like platform_get_current_validators or platform_get_pending_validators. No exclusions or comparison to siblings are provided, so the agent must infer the distinction from the name and description.
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.
