Get the CB58-encoded blockchain ID for a given blockchain alias (e.g., "X", "P", "C").
| Name | Required | Description | Default |
|---|---|---|---|
| alias | Yes | The blockchain alias (e.g., "X", "P", "C", or a full blockchain name) | |
| network | No | The Avalanche network to query (default: mainnet) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the operation ('Get') and output encoding, but does not mention read-only guarantees, error behavior, network default, authentication requirements, or any side effects. This leaves the agent uninformed about important 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 filler. It immediately states the action and object, and the parenthetical examples make the input format clear without extra prose.
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-only getter with a 2-parameter schema fully described, the description plus schema is sufficient to understand the tool's core behavior. It explains the return type (CB58-encoded blockchain ID) and the schema covers parameter defaults and enums. Minor gaps like error cases prevent a perfect score.
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% with detailed descriptions for both 'alias' and 'network', including examples and enum values. The description adds only marginal context (the CB58 output encoding) and does not deepen the meaning of the parameters beyond the schema, so the baseline of 3 is appropriate.
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 uses a specific verb ('Get') and resource ('CB58-encoded blockchain ID') with concrete alias examples ('X', 'P', 'C'). This clearly identifies the tool's function and distinguishes it from sibling tools like info_get_network_id or blockchain_lookup_chain.
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 that the tool should be used when you have a blockchain alias and need its CB58-encoded ID, but it does not explicitly state when to use it versus alternative tools or mention any exclusions/prerequisites. Sibling tools such as blockchain_lookup_chain might overlap, and no guidance is given for choosing between them.
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.
