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get_asset_info

Read-onlyIdempotent

Get complete properties and configuration for any asset on the Klever blockchain (KLV, KFI, KDA tokens, NFT collections). Returns supply info, permissions (CanMint, CanBurn, etc.), roles, precision, and metadata. Note: string fields like ID, Name, Ticker are base64-encoded in the raw response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetIdYesAsset identifier (e.g. "KLV", "KFI", "USDT-A1B2", "MYNFT-XY78").
networkNoNetwork to query. Options: "mainnet", "testnet", "devnet", "local". Defaults to server default (mainnet).

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safe-read nature is covered. The description adds valuable behavioral context by warning that string fields (ID, Name, Ticker) are base64-encoded in the raw response, which is not inferable from annotations or schema. This goes beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences deliver all essential information: the first covers purpose and scope, the second highlights the base64 encoding caveat. There is no redundant phrasing or filler, making it ideal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description enumerates the return contents (supply info, permissions, roles, precision, metadata) and the encoding caveat. Combined with thorough annotations and schema, this provides sufficient context for an agent to understand what will be returned and how to interpret it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents both parameters comprehensively (assetId with examples, network with enum values and default), achieving 100% coverage. The description adds no further parameter-level detail, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gets complete properties and configuration for assets on the Klever blockchain, specifying asset types (KLV, KFI, KDA tokens, NFT collections). This verb-resource-scope combination distinctly differentiates it from sibling tools like get_account or get_balance.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on what the tool does and the types of assets it covers, but does not explicitly mention alternatives or when not to use it. Since the name and description make its use case self-evident, the lack of exclusions is acceptable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.2/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count4/5

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.

Completeness5/5

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.