List Avalanche Community Proposals with structured fields, optionally filtered by status (Activated, Implementable, Proposed, Stale, Withdrawn) or track (Standards, Best Practices, Meta, Subnet).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of ACPs to return (default: 50) | |
| track | No | Filter by ACP track. Matches Standards, Best Practices, Meta, or Subnet. | |
| status | No | Filter by ACP status (case-insensitive) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions returning structured fields and filtering, but does not include details about pagination (despite the limit parameter), default behavior, ordering, or error conditions. The read-only nature is implied but not explicitly stated.
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, well-structured sentence that states the core function and optional filters. It is concise, front-loaded, and free of unnecessary words, earning a top score for structure.
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 list tool, the description covers the core function and main filters. However, there is no output schema, and the description does not elaborate on the 'structured fields' or mention the limit parameter and pagination behavior. This leaves notable gaps in 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% description coverage for all three parameters, including enums for status and track. The description lists status and track values in prose, which is redundant with the schema, and adds no new information about the limit parameter or defaults. This meets the baseline expected when the schema is comprehensive.
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 the specific verb 'List' and identifies the resource 'Avalanche Community Proposals' with optional filters, making its purpose clear. It names the object and action unambiguously, though it does not explicitly distinguish from sibling tools like acp_lookup or info_acps.
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 listing ACPs, optionally filtered by status or track, and lists filter values. It does not state when to prefer this tool over alternatives or provide exclusions, so guidance is implicit rather than explicit.
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.
