Search body-level chunks across Avalanche documentation, academy courses, integrations, and blog posts. Returns source citations and matching excerpts.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of chunk results (default: 10) | |
| query | Yes | The search query | |
| source | No | Filter by documentation source (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It discloses that the tool returns source citations and matching excerpts, which is helpful. However, it does not explicitly state read-only behavior, pagination, or any other potential side effects, though none are expected for a search tool.
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 two sentences, front-loaded with the primary action and followed by the output. Every word contributes, making it concise and well-structured.
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?
The description covers the core functionality and return type, which is sufficient for a search tool without an output schema. However, given the large sibling list and the presence of a similar tool (avalanche_docs_search), a note on differentiation or typical use cases 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 (query, limit, source), including clear descriptions. The tool description adds minimal value beyond the schema, only mentioning the sources in a general way. The baseline of 3 is appropriate since the schema does the heavy lifting.
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 function: searching body-level chunks across specific documentation sources and returning citations and excerpts. However, it does not explicitly differentiate from the sibling tool 'avalanche_docs_search', which appears to have a similar purpose.
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 like docs_fetch or avalanche_docs_search. The description implies usage for searching but does not state exclusions or preferred scenarios, leaving the agent without clear selection criteria.
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.
