attach_foundation

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

No annotations provided; description carries full burden. Discloses draft nature, LLM validation, no credit until confirmed, and return structure. Could mention side effects or permissions but adequate.

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 short paragraphs, front-loaded purpose, efficient example embedded. Every sentence adds value. No fluff.

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 complexity (draft edge creation), description covers input, process, and output. References sibling tool for context. Output schema exists so return shape is covered. 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?

Schema coverage 75% (server_version missing description). Description provides JSON example for selections, clarifying parameter usage beyond schema. Adds context for model_id and foundation_model_id but omits server_version explanation.

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 creates draft delegation edges for selected (objective, control) pairs, with specific input format and outcome. Distinguishes from sibling propose_attach_foundation by noting this is the operator-confirmed subset.

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 selections come from propose_attach_foundation, indicating when to use. No explicit alternatives or when-not-to-use, but context is sufficient for correct invocation.

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