delimit_social_target

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

With no annotations provided, the description carries full burden. It discloses deduplication across runs, loop execution, and manual check requirement for NamePros. It also explains target classification logic. However, it does not mention rate limits, authentication needs, or specific side effects of scanning external APIs, which would improve transparency.

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?

The description is well-structured with a clear header, bold tool chaining rule, and organized details. Every sentence adds value, but it could be slightly more concise. The front-loading of purpose and critical rule is effective.

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 the tool's complexity (7 parameters, output schema exists), the description covers purpose, usage, behavior, and parameter semantics. It does not cover error handling or potential failures, but overall it provides sufficient context for an AI agent to use the tool correctly and chain it with others.

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?

Input schema coverage is 100%, so baseline is 3. The description adds value by explaining the tool's action modes ('scan', 'list', 'stats') corresponding to the 'action' parameter, and the flags 'draft_replies' and 'create_ledger' for auto-processing. This enriches the schema's brief descriptions.

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 explicitly states the tool's purpose: 'Discover engagement opportunities across platforms (Pro).' It clearly identifies the resource (social engagement targets) and the action (discover/scan). It lists specific platforms and target classifications, making it distinct from sibling tools like delimit_social_post for drafting or delimit_ledger_add for ledger items.

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 provides explicit tool chaining rules: after scanning, the AI must process results based on target type. It specifies actions for 'reply', 'strategic', and 'both' targets, and mentions running in a loop for continuous discovery. This gives clear when-to-use and how-to-proceed guidance, including a flag for a platform requiring manual check.

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