create_clientCreate a new entity (company) in the organization. Requires a Manager-role key. Use only when the user explicitly asks to set up a new entity; show them the name you will create first.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| business_model_code | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false (write operation) and destructiveHint=false. The description supplements this with a 'Manager-role key' requirement and the need to show the name to the user first, adding meaningful context about auth and confirmation behavior. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of three concise sentences, front-loaded with the core purpose, then the auth requirement, and finally the usage/confirmation guideline. Every sentence adds value with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, auth requirements, and a usage constraint, which is good given the simple tool signature. However, it omits the optional business_model_code parameter entirely and provides no indication of return values or post-create behavior, leaving some important context for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only vaguely references 'the name' but does not explain the required 'name' parameter or the optional 'business_model_code' parameter, their constraints, or their purpose. This leaves an agent without crucial parameter-level understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Create') and a clear resource ('new entity (company)'), which distinguishes it from sibling tools like create_cost_centre and create_profit_centre that create different resource types. It clearly identifies what the tool does without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives an explicit condition for use: 'Use only when the user explicitly asks to set up a new entity' and adds a required confirmation step ('show them the name you will create first'). However, it does not mention alternative tools or when not to use it beyond the 'only when' clause, so it misses the top tier.
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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Each tool targets a distinct resource or action — get_* reads, save_* writes, confirm_* approves, preview_* shows consequences before approval. Even the management-data trio (budgets, allocations, variance) is cleanly separated by surface. Two-step flows like preview_chart_rebaseline → confirm_complete_chart are clearly sequenced, so an agent won't confuse the stages.
Tool names follow a highly consistent verb_noun pattern: get_* for reads, list_* for discovery, save_* for section writes, confirm_* for approvals, create_* for new entities/centres, preview_* for pre-approval checks. The few one-offs (ingest_upload, upload_trial_balance, set_header_row) still fit the verb-first convention. No camelCase or style mixing.
At 67 tools this is well past the 'too many' threshold. While the Schedule III domain genuinely is broad — statutorily mandated sections, two-phase approval flows, readiness checks, and a separate management-data area — the surface is heavy; an agent will spend real effort just surveying the tool list. Some consolidation of the save_reserves/provisions/assets movements or merging preview+confirm pairs is possible.
The surface covers the full lifecycle: upload → mapping/costing → grouping → capture (all statutory sections) → declarations → readiness → generate → finalise → download, plus entity setup and consolidated statements. Minor gaps: no tool directly exposes historical version diffing beyond list_snapshots, and the management-data section (budgets, allocations, variance) feels bolted on rather than integral to the core flow.