Get transaction details by hash from the Klever blockchain. Returns sender, receiver, status, block info, contracts, and receipts. Uses the API proxy for indexed data.
| Name | Required | Description | Default |
|---|---|---|---|
| hash | Yes | Transaction hash (hex string). | |
| network | No | Network to query. Options: "mainnet", "testnet", "devnet", "local". Defaults to server default (mainnet). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds useful behavioral context beyond that: it mentions the use of the API proxy for indexed data and lists the exact categories of returned data, giving the agent a clearer picture of what to expect. No contradiction exists.
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 concise sentences. The first sentence front-loads the core purpose and return contents; the second adds a relevant detail about the data source. Every word earns its place with no redundancy or fluff.
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 tool's simplicity (two parameters, no output schema), the description is complete. It covers what the tool does, what it returns, and how it accesses data. The annotations and schema handle safety and parameter details, so nothing critical is missing.
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 is 100%, with both parameters (hash and network) fully described in the input schema. The description adds minimal extra meaning beyond the schema—it reiterates that the lookup is 'by hash' but does not provide additional syntax, constraints, or examples. Thus, baseline 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 clearly states the tool's purpose: 'Get transaction details by hash from the Klever blockchain.' It specifies the resource (transaction) and actionable verb ('get'), then enumerates the return fields (sender, receiver, status, block info, contracts, receipts), distinguishing it from sibling tools like get_block or get_account.
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 provides clear context on when to use the tool: when you need transaction details by hash. It also mentions the data source ('Uses the API proxy for indexed data'), which implies the appropriate environment. However, it does not explicitly mention alternatives or when not to use it, so it stops short of full 5.
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 clearly distinct purposes, such as get_balance for token balances, analyze_contract for code analysis, and init_klever_project for project scaffolding. However, there is some overlap between query_context and search_documentation, both of which search the knowledge base, which could cause confusion about which to use for specific queries.
The naming follows a consistent verb_noun pattern throughout, such as get_balance, analyze_contract, and init_klever_project. Minor deviations exist, like add_helper_scripts (verb_adjective_noun) and enhance_with_context (verb_preposition_noun), but overall, the pattern is clear and predictable.
With 16 tools, the count is slightly high but reasonable for the Klever VM domain, which covers blockchain queries, smart contract development, and knowledge base management. It provides comprehensive coverage without being overwhelmingly large, though it could be streamlined by merging overlapping tools.
The tool set offers complete coverage for Klever VM development, including project setup (init_klever_project, add_helper_scripts), contract analysis and querying (analyze_contract, query_sc), blockchain data retrieval (get_balance, get_transaction, get_block), and knowledge base access (query_context, search_documentation). No obvious gaps are present for the intended scope.
