Skip to main content
Glama

company_payroll

Inspect payroll records or advance them through lifecycle stages while verifying supplied proofs and keeping provider effects external.

Instructions

Inspect or advance payroll through its scoped lifecycle; supplied proofs are verified and provider effects remain external.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nowNo
engineNo
operationNolist
entity_refNo
project_idYes
bundle_jsonYes
payload_jsonNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.1.1

TDQS

C2.2/5.0
Behavior2/5

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

No annotations are present, so the description carries the full behavioral burden. It discloses that supplied proofs are verified and provider effects remain external, which is useful but incomplete: it does not state what changes 'advance' makes internally, whether the operation is reversible, what permissions are required, or what failures look like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and avoids filler, but it is more economical than truly clear. The phrase 'scoped lifecycle' and the 'provider effects remain external' caveat add some information yet still feel abstract and jargon-heavy relative to the rest of the tool's needs.

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

Completeness2/5

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

Even though the tool has an output schema, there are no annotations and 7 parameters with no descriptions. The description alone is not enough for an agent to choose a correct operation value, understand what 'list' or 'advance' requires, or construct bundle_json/payload_json, so contextual completeness is low.

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

Parameters1/5

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

This is a 7-parameter tool with 0% schema description coverage, and the description contributes no parameter meaning. It does not explain operation, bundle_json, payload_json, entity_ref, or how 'proofs' map to any field, leaving an agent unable to construct the required arguments with confidence.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a resource (payroll) and a broad action pair ('inspect or advance'), but 'scoped lifecycle' is vague and not elaborated. It also does not differentiate this tool from payroll-related siblings such as finance_payroll or company_pay_run, so an agent gets only a general sense of what it does.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool over alternatives, which lifecycle stage to target, or how to choose between inspecting and advancing. The description does not explain when it applies or when a different payroll tool should be used.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RPasquale/lightbulb-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server