context_status

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

Without annotations, the description covers key behaviors: read-only status check (implied by 'check'), and outputs message count, token usage, bloat indicators. No mention of side effects, but it's a non-destructive query.

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?

Two succinct sentences plus conditional guidance. Every sentence provides necessary information without redundancy. Front-loaded with the core purpose.

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 no output schema, the description adequately hints at return values (message count, token usage, bloat indicators). It aligns with siblings and covers typical usage scenarios. Could be slightly more specific about 'bloat indicators' but overall comprehensive.

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?

The single parameter `conversation_id` is described with additional context: default behavior (most recent conversation) and how to find the ID from the status bar. Schema coverage is 100%, and the description adds value 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's purpose: to check context usage, including message count, token usage, and bloat indicators. It distinguishes itself from siblings like `prune_context`, which modifies context.

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?

Explicitly states when to use: 'when starting a complex task or when you suspect context is getting large.' Provides an alternative action with `prune_context` if usage exceeds 70%, offering clear decision guidance.

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