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Get Talonic Credit Balance

talonic_get_balance
Read-only

Check your workspace credit balance, EUR value, tier, 30-day burn rate, and projected runway to confirm headroom before large batch operations.

Instructions

Read the workspace's Talonic credit balance, EUR value, tier, 30-day burn, and projected runway.

USE WHEN: the user asks about credits/budget, or before a large batch when you want to confirm headroom. NOT FOR: the per-call cost of a single extraction (that is on the talonic_extract response). ARGS: none. RETURNS: balance_credits, balance_eur, tier, burn_rate_30d_credits, projected_runway_days (-1 = no recent usage), tier_resets_at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
balance_creditsYesCurrent credit balance.
balance_eurYesCurrent balance in EUR (two decimals).
burn_rate_30d_creditsYesTotal credits consumed in the trailing 30 days.
projected_runway_daysYesProjected days of runway at the current 30-day average burn. `-1` when burn is zero (cannot compute).
tierYesAPI tier of the workspace.
tier_resets_atYesISO 8601 timestamp of the next monthly tier reset.
Behavior5/5

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

Annotations already mark it read-only. The description adds value by detailing returned fields and noting that projected runway is -1 when no recent usage. No contradiction with annotations.

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?

Description is concise: a single introductory sentence followed by structured USE WHEN, NOT FOR, ARGS, and RETURNS sections. Every sentence is informative and earns its place.

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 the tool's simplicity (read-only, no parameters, documented output schema), the description covers all necessary context: what is returned, when to use, and what not to use for. No gaps.

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?

Input schema has 0 parameters (100% coverage). Description explicitly states 'ARGS: none.' Baseline for 0 parameters is 4, and the tool meets that standard without needing further parameter documentation.

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 it reads the workspace's Talonic credit balance, EUR value, tier, 30-day burn, and projected runway. The verb 'Read' and specific resource details make purpose unambiguous. It naturally distinguishes from credit-related queries that would go to talonic_extract.

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?

Explicit USE WHEN and NOT FOR sections provide clear guidance: use when user asks about credits/budget or before a large batch; not for per-call cost (pointing to talonic_extract). This effectively differentiates from sibling tools.

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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