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company_job_costing

Build job costing from work orders and contractor engagements. Get per-job estimates, actuals, variances, labor hours, on-time rates, asset costs, repair-or-replace reviews, and invoice comparisons.

Instructions

Build the sealed job costing over the window from every persisted work order and contractor engagement: per job the estimate, actual, variance, cost mix, labour hours, and on-time; per kind the estimating bias, overrun and on-time rates; per asset the total cost and the repair-or-replace review; per contractor approved work against invoices and payments (payload: optional window_start, window_end).

Input Schema

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.2

TDQS

B3.4/5.0
Behavior3/5

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

It adds useful behavioral context: the costing is 'sealed', scoped 'over the window', and built from all persisted work orders and contractor engagements, suggesting an aggregate/report-building operation. With no annotations, though, it leaves side effects, persistence, permissions, and idempotency undisclosed.

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

Conciseness4/5

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

It is densely informative and front-loaded with the action, and the semicolon-separated output list avoids filler. The trailing parenthetical about payload is easy to miss, so structure is good but not ideal.

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?

Despite the rich output list, the description omits parameter semantics, when/why to choose it, and behavioral safety, all of which matter here because there are 7 parameters, no annotations, and 0% schema coverage. The output schema mitigates the missing return description, but the inputs remain under-specified.

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

Parameters2/5

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

Schema coverage is 0% and the description only hints at 'payload: optional window_start, window_end'. It does not explain the required project_id and bundle_json, nor the generic now/engine/operation/entity_ref parameters, so an agent is left guessing about how to construct the call.

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 names a specific action ('Build'), a concrete artifact ('sealed job costing'), and the data sources ('every persisted work order and contractor engagement'), then enumerates the report's sections. This makes it easy to differentiate from siblings like company_job_quote or company_work_orders even without an explicit comparison.

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

Usage Guidelines3/5

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

The tool's intended context is implied: use it when a job costing snapshot over a window is wanted. However, it never states when not to use it or which sibling tool should be preferred, leaving selection to inference.

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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