search_context

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

With no annotations, description must carry the full burden. It discloses search sources (Jira, transcripts, documentation) and confirms input is natural language. However, it does not mention response format, scope limitations, or any behavioral traits like read-only nature. Adequate but not comprehensive.

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?

Three sentences efficiently conveying purpose, examples, and input format. No fluff or 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 simple tool with one parameter and no output schema, description covers sources and usage examples adequately. Could mention what kind of results are returned, but not essential for selection decision.

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 100% (single query parameter with description 'Natural language question or search terms'). The description essentially repeats this as 'Input is a natural language question', adding no new 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?

Description clearly states it's for freeform questions about codebase, architecture, or past decisions, searching across Jira, transcripts, and documentation. Distinguishes from siblings like devscontext_status or get_standards by emphasizing freeform natural language queries.

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 provides example questions ('how do we handle errors?', etc.) indicating when to use. Does not explicitly list when not to use or alternatives, but the examples give clear context for appropriate use cases.

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