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VARRD — Statistically Validated Trading Edges + AI Research Engine

check_balance

Read-onlyIdempotent

Check your credit balance and see available credit packs. Free — no credits consumed. Also auto-detects completed payments — call this after your user pays via a checkout link to confirm credits were added. If payment went through, the response includes recovered_cents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
credit_packsNoAvailable credit packs for purchase
balance_centsNoCurrent credit balance in cents
recovered_centsNoCredits recovered from completed payments (if any)

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds valuable context: 'Free — no credits consumed' and the auto-detection behavior with 'recovered_cents' in the response. This enriches the agent's understanding of side effects and return values.

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?

Three focused sentences, each earning its place: first states the core purpose, second addresses cost, third provides a critical usage scenario and expected response. No redundancy or filler.

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?

The description fully covers the tool's purpose, usage context, and important behavioral nuances. With output schema available and annotations present, no additional explanation is needed for a zero-parameter tool.

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?

The tool has zero parameters and the schema is empty, so there's nothing to explain. Baseline for 0 params is 4, and the description appropriately mentions the response field 'recovered_cents' which aligns with the 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?

The description uses specific verbs ('Check', 'see', 'auto-detects') and clearly identifies the resource ('credit balance', 'credit packs', 'completed payments'). It distinguishes from siblings like buy_credits by focusing on checking and payment confirmation, not purchasing.

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 states the tool is free and safe to use, and gives a concrete scenario ('call this after your user pays via a checkout link to confirm credits were added'). This provides clear when-to-use guidance and implies alternatives like buy_credits for purchasing.

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

A4.4/5.0
Disambiguation4/5

Most tools have distinct purposes, but 'autonomous_varrd_ai' and 'varrd_ai' could cause confusion despite clear descriptions. 'varrd_edges' vs 'varrd_ai' are distinct. Overall, minor overlap but manageable.

Naming Consistency3/5

Names mix snake_case verbs and noun phrases, and the 'varrd_' prefix is inconsistently applied. 'autonomous_varrd_ai' deviates from the verb_noun pattern. Still readable.

Tool Count5/5

9 tools is well-scoped for the server's purpose—covers research, credit management, results browsing, and session control without bloat.

Completeness4/5

Covers core workflows: hypothesis generation, testing, browsing live edges, and managing credits. Missing explicit update/delete capabilities for hypotheses, but overall surface is sufficient.