paperclip_get_costs_by_project

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

Annotations already declare readOnlyHint=true, so description is not required to reemphasize safety. The description adds useful behavioral context such as error codes (401, 403) and hints about authentication. However, it does not mention pagination or performance limitations, which could be added.

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 is concise with clear sections (Args, Returns, Examples, Error Handling). Every sentence adds value, and the structure is easy to parse for an AI agent.

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?

Given the low complexity (one optional parameter, no output schema), the description fully covers return format and error handling. It provides enough context for correct invocation without requiring additional documentation.

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 coverage is 100% and the schema already describes the parameter well. The description adds minor details like default value and output format human-readable vs structured, but does not significantly enhance meaning beyond the schema.

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 clearly states the tool retrieves 'LLM token costs broken down by project for the current company', specifying the verb, resource, and scope. It also distinguishes from the sibling tool paperclip_get_costs_by_agent by mentioning when not to use it.

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 'Examples' section explicitly states when to use ('comparing spend across projects') and when not to use ('need agent-level costs'), directing to the alternative tool paperclip_get_costs_by_agent. This provides excellent guidance.

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