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

Annotations already declare the write/open-world/non-idempotent profile, and the description adds genuinely useful behavior: the reply is sent instantly with no AI involvement, placeholders like [address] are not substituted, and editor role is required. It does not cover keyword-collision or duplicate-rule behavior, so it falls just short of full disclosure.

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, front-loaded with the core create-rule semantics, followed by the highest-risk caveat (real text, no placeholders) and the permission requirement. No filler or repetition.

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?

With no output schema and 7 parameters at 86% schema coverage, the description supplies the crucial behavioral facts an agent needs: instant non-AI send, verbatim text, editor role. It could say more about rule activation state or multiple-keyword interaction, but nothing critical is missing.

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 86%, so the schema already documents match, frequency, project_id, and first_message_only semantics including enum meanings. The description only adds an illustrative keyword-to-reply example, so the schema carries the parameter burden and baseline 3 applies.

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?

States a specific verb and resource ('Create a rule') plus the exact trigger/effect pair: a client keyword causes an instant, non-AI reply. This clearly separates it from AI-driven content tools like dosai_add_knowledge_text and dosai_add_followup_step.

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 conveys the usage context ('when a client writes one of the words... without the AI') and the example ('the word "price" gets the price list') makes the intended scenario concrete. It stops short of naming a sibling alternative or stating exclusions, so it is clear context without explicit routing.

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