get_communityGet all concepts belonging to one documentation community (a cluster of related concepts detected in the knowledge graph, e.g. all wallet-related or all node-operation concepts).
| Name | Required | Description | Default |
|---|---|---|---|
| community_id | Yes | Numeric community ID, as returned in the "community" field by query_graph(), get_node() or get_neighbors(). |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, covering the safety profile. The description adds domain context (what a community is) but no additional behavioral traits such as side effects, prerequisites, or limits. No contradiction found.
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?
One sentence, about 30 words, front-loaded with the action and resource, followed by a concise parenthetical clarification. No wasted words.
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 one-parameter read-only tool with a detailed parameter schema and output schema, the description sufficiently defines the scope (all concepts in a community) and provides illustrative examples. It could be more complete with explicit usage guidance, but it is not lacking in essential information.
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 coverage for the single parameter is 100%, with a detailed description explaining that community_id comes from the 'community' field of other graph functions. The tool description itself does not add extra parameter-level meaning, so it stays at the baseline.
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 verb ('Get') and resource ('all concepts belonging to one documentation community'), with a helpful parenthetical defining what a community is and giving concrete examples ('wallet-related or node-operation concepts'). This distinguishes it from sibling tools like get_node (single node) and get_neighbors (adjacent nodes).
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: you call this when you have a community_id and want all concepts in that community. However, it does not explicitly mention when not to use it or name alternatives, relying on the user to infer distinctions from the sibling list.
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.
Most tools have distinct purposes, but there is slight overlap between register_on_gonka and get_signup_link (both return signup links) and between get_pricing, calculate_savings, compare_providers, and suggest_model_for_task (all deal with pricing). Descriptions help differentiate, but boundaries are not perfectly sharp.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., calculate_savings, get_available_models, search_docs). No mixed conventions or abbreviations. Naming is predictable and clear.
18 tools is on the higher side, but each serves a specific function within pricing, documentation, and signup workflows. The count feels slightly bloated, particularly with closely related documentation graph tools, but overall still well-scoped.
The tool set comprehensively covers the domain of Gonka Network pricing: live pricing, comparisons, savings calculations, model recommendations, documentation search (graph and full-text), trial key provisioning, and signup links. No obvious gaps for the stated purpose.