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prismhr-mcp

payroll_superbatch_status

Summarize a client's payroll cycle health: count batches by status (open/pending/posted/voided) and total gross payroll across a date range.

Instructions

Summarize a client's payroll cycle health across a date range.

Use for morning-of-pay status checks: "how's Acme's payroll looking this week" or "show me everything that's open vs. posted for client XYZ this quarter". Counts batches by status (open / pending / posted / voided) and totals gross payroll across them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
client_idYesThe client.
start_dateYesFirst day to include (YYYY-MM-DD).
end_dateYesLast day to include (YYYY-MM-DD).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
client_idYes
start_dateYes
end_dateYes
batch_countYes
total_vouchersYes
total_grossYes
open_batch_countYes
pending_batch_countYes
posted_batch_countYes
voided_batch_countYes
batchesYes
Behavior4/5

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

Although no annotations are provided, the description transparently states the output: counts by status and totals gross payroll. It does not mention potential limitations or the read-only nature, but it gives a good sense of behavior.

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?

The description is three sentences, front-loaded with the main purpose, followed by usage examples and output details. Every sentence is informative and there is no superfluous content.

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?

Given the tool's moderate complexity (3 params, output schema present), the description explains what the tool does and its output format adequately. It could mention date range limits or performance, but it is sufficiently complete for typical use.

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?

Schema descriptions are minimal, but the tool description adds meaning by explaining how the parameters combine to produce summary counts and totals, going beyond the parameter names and types.

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 a specific verb 'summarize' and resource 'client's payroll cycle health across a date range', clearly distinguishing it from sibling tools like payroll_batch_status which likely handles individual batches.

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

Usage Guidelines4/5

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

Provides explicit use cases like 'morning-of-pay status checks' and example queries, giving clear context for when to use this tool, though it does not explicitly state when not to use it or name alternative 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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