delimit_social_target

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It transparently states that the tool scans multiple platforms, deduplicates across runs, classifies targets as reply/strategic/both, and suggests loop usage. It does not mention potential side effects like rate limiting or authorization requirements, but for a scanning tool these are less critical. Overall, it is fairly transparent about its core behavior.

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 separation of the purpose, an important chaining rule, and then additional details. Every sentence serves a purpose, and the information is front-loaded (purpose first, rule second). It is appropriately sized for the complexity of the tool.

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 complexity (7 parameters, output schema exists, many siblings), the description covers purpose, usage guidelines, tool chaining, target classification, platform list, loop usage, and deduplication. It explains the classification system and the corresponding required actions. Although an output schema exists, the description does not need to elaborate on return values since that is covered by the schema. It is sufficiently complete for an agent to select and invoke the tool correctly.

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 each parameter having a clear description. The tool's description does not add significant additional meaning beyond what the schema already provides for parameters. It mentions the action types ('scan', 'list', 'stats') implicitly but not explicitly, and the parameters like 'draft_replies' and 'create_ledger' are adequately described in the schema. Baseline 3 is appropriate.

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: 'Discover engagement opportunities across platforms (Pro).' It specifies the verb (discover), resource (engagement opportunities), and mentions scanning specific platforms and classifying targets. It distinguishes from sibling tools like delimit_social_post by including a mandatory tool chaining rule that tells the AI to use delimit_social_post after scanning for 'reply' targets, setting clear boundaries.

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 guidance on when and how to use the tool, including a mandatory tool chaining rule ('After scanning, the AI MUST immediately process results...'), instructions to run in a '/loop for continuous discovery', and a note that 'NamePros flagged as manual_check_needed'. It specifies exactly what actions to take for each target classification, leaving no ambiguity.

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