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setup_status

Check system status and available data at conversation start to determine which analyses are possible. Use this to verify API connectivity and data readiness before proceeding.

Instructions

One-shot setup diagnostic. Call this at the start of every conversation, and any time the user asks for analysis but you're unsure what data is available. Returns: API key state, data counts (transactions / balance / flow / prices / snapshots / FX), profile, next_steps for onboarding, capabilities (which kinds of analysis are currently possible), and analyst_context (the persona, principles, data_gating rules, and reasoning frameworks). Treat capabilities as a hard gate — if a required capability is false, follow the matching data_gating rule instead of fabricating an answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully covers what the tool returns: API key state, data counts, profile, next steps, capabilities, and analyst_context. It also explains how to treat capabilities as a hard gate, preventing fabrication.

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?

Concise yet comprehensive single paragraph. Front-loaded with purpose and usage, followed by return values and critical instructions. No wasted words.

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?

Given zero parameters and no output schema, the description provides all necessary context: purpose, when to call, what it returns, and how to interpret results. Complete for the tool's role.

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

Parameters4/5

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

No parameters exist, so baseline is 4. The description adds value by detailing the return fields, which compensates for missing output schema.

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?

Clearly identifies as a one-shot setup diagnostic tool. Distinguishes from sibling tools like add_balance or show_txns which operate on specific data, while this tool checks data availability and capabilities.

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

Usage Guidelines5/5

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

Explicitly instructs to call at the start of every conversation and any time unsure of data availability. Provides clear context for use without needing exclusion criteria.

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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