animica_credit_balance
FREE: balance, expiry and spend history for a prepaid credit token.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| credits | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Animica
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- Added
TDQS
C2.4/5.0
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description discloses no behavioral traits such as read-only status, authentication needs, rate limits, or side effects. The 'FREE:' note is ambiguous and insufficient to convey safety or cost behavior. The description carries the full burden here but fails to provide any transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose. It is front-loaded with the 'FREE:' label, which is not essential but does not waste space. It could be improved by incorporating param guidance, but for its length, it earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one optional param, output schema exists), the description is incomplete because it omits explanation of the 'credits' parameter and any behavioral context. The output schema may help with return values, but the input side is left opaque, making effective invocation guesswork.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'credits' (string, optional, default '') with 0% description coverage. The description does not explain what this parameter represents (e.g., a token identifier). The agent cannot determine how to use it, and the description adds no meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'balance, expiry and spend history for a prepaid credit token,' clearly identifying the resource (credit token) and the data provided. This distinguishes it from sibling tools that deal with AI, blockchain, or other services. A small improvement would be an explicit verb like 'get' or 'retrieve,' but the intent is clear enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, or whether there are prerequisites or restrictions. The prefix 'FREE:' hints at cost behavior but does not constitute usage advice. The agent receives no help with tool selection beyond the purpose.
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
B3.1/5.0
Disambiguation4/5
Most tools have clearly distinct purposes (AI inference, blockchain queries, notarization, quantum randomness, web fetching, etc.). The only minor overlap is between animica_ai_ask and animica_web_ask (both answer questions), but the former is a general AI query and the latter specifically about a single web page, so they are reasonably disambiguated.
Naming Consistency5/5
All tools follow a consistent animica_{domain}_{action} pattern (e.g., animica_ai_ask, animica_chain_block, animica_quantum_beacon_latest). The snake_case convention is uniform, and each name clearly indicates the sub-system and the operation.
Tool Count4/5
22 tools is on the higher side but still reasonable given the broad scope (blockchain, AI, notarization, quantum, web, studio). Each tool serves a distinct purpose, and the count reflects the diverse feature set without being excessive.
Completeness3/5
The tool surface covers the main advertised capabilities (AI inference, blockchain reading, notarization, quantum randomness, web fetching, studio). However, there are notable gaps: no tool for writing to the chain (e.g., sending a transaction), no tool for listing/creating credit tokens, and no AI model management beyond listing. The read-only blockchain tools are thorough but lack write operations.