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get_agent

Evaluate ANY token running on VaultBags as an autonomous agent, by SPL token mint: its Autonomy Score, its passport (identity, surfaces, on-chain receipts) and its treasury. The score is split into protocolScore (guarantees every VaultBags agent inherits: a brain that decides daily, decisions stamped on-chain, the firewall) and projectScore (what THAT token earned on its own: distribution cycles that paid its holders, and the length of its own public record). A freshly launched token has a strong protocol side and a projectScore of 0, so never read the composite alone as evidence of a track record. Read-only public data.

Input Schema

NameRequiredDescriptionDefault
mintYesThe agent's SPL token mint address (base58).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it declares 'Read-only public data' for the safety profile, explains that the score decomposes into protocolScore (inherited guarantees) and projectScore (token-specific track record), and warns that fresh tokens show projectScore 0. It omits error behavior, rate limits, and pagination, keeping it short of a 5.

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?

Front-loaded with the verb and resource, and the score-composition caveat earns its place by preventing misinterpretation of the result. The middle clause about protocol guarantees is somewhat verbose but still functional; no sentence is pure waste.

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

Completeness4/5

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

There is no output schema, so the description must convey return values, and it does: Autonomy Score split into protocolScore/projectScore, plus passport (identity, surfaces, on-chain receipts) and treasury. That covers the shape of the response; only edge-case behavior (errors, missing mint) is absent.

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?

Schema description coverage is 100%, so the base58 SPL mint format is already documented in the schema. The description only restates the parameter as 'by SPL token mint' and adds that it accepts ANY VaultBags token, which is marginal semantic value over the schema. Baseline 3 applies.

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?

States a specific verb and resource: evaluate any VaultBags token as an autonomous agent by SPL mint, returning its Autonomy Score, passport, and treasury. However, it never distinguishes itself from close siblings like get_agent_passport, get_autonomy, or get_project_treasury, so an agent must infer that this is the composite view rather than a scoped one.

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

Usage Guidelines3/5

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

The trigger is implied (look up an agent by mint) and there is one genuine interpretive guideline: never read the composite score alone for a freshly launched token. But it gives no when-to-use-vs-alternatives guidance against the many overlapping sibling tools, leaving selection to inference.

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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