Ask an AL-Go Specialist

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

With no annotations provided, the description carries the full burden. It discloses auto-selection of the best specialist and the optional specialist parameter for specific personas. However, it does not describe the nature of the answer (e.g., AI-generated or human-like), potential limitations, or any side effects of consultation.

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, each serving a distinct purpose: stating the tool's role, explaining behavior, and giving usage triggers. No redundant or filler content.

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, usage, and parameter behavior well. However, since there is no output schema, it omits any indication of what the specialist returns (e.g., answer format, length, or whether it's a conversation). This gap reduces completeness for the 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 coverage is 100% with basic descriptions. The description adds value by explaining that the specialist is auto-selected if omitted and provides example values for the specialist parameter (e.g., 'freddy', 'casey', 'rex'), which clarifies usage 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: consulting an AL-Go domain specialist for expert guidance on specific topics like workflows, CI/CD, releases, testing, and app development. It distinguishes the tool from siblings by emphasizing specialized AL-Go knowledge and auto-selection of specialists.

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 explicitly says 'Use this whenever the user asks about AL-Go or addresses a specialist directly' and provides concrete examples of how to invoke the specialist (e.g., '@alg-freddy'). However, it does not explicitly mention when not to use the tool or suggest alternatives.

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