find_opportunities

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

No annotations are provided, so the description carries the full transparency burden. It discloses that the tool 'Uses AI to analyze each tweet,' lists the three scoring criteria, describes the output as scored tweets with suggested reply angles, and notes the required SHIPPOST_API_KEY. It doesn't mention rate limits or side effects, but no mutating behavior is implied.

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 and front-loaded: a one-sentence summary, a concise bullet list of scoring criteria, an output statement, and an auth note. Every section earns its place with no redundant filler.

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 presence of an output schema and fully described optional parameters, the description covers the essential ground: purpose, behavior, input context, output shape, and authentication. It could be more complete with an explicit 'does not post or like anything' note, but the current level is sufficient for a discovery tool.

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?

The input schema already fully documents both parameters (niche and max_results) with clear descriptions and defaults, so the baseline is 3. The description adds little parameter-specific detail beyond tying 'niche' to the relevance scoring criterion, which is helpful but not necessary.

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 opens with a specific verb+resource: 'Scan my timeline and find the best tweets to reply to, scored by relevance.' This clearly distinguishes it from sibling tools like get_timeline (raw timeline retrieval) or reply_to_tweet (posting a reply), positioning it as an AI-scored opportunity finder.

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 usage context is clear: use this when you want AI-scored reply opportunities from your timeline, not when you need raw timeline data or immediate posting actions. It doesn't explicitly name alternatives or exclusions, but the description's task framing makes the intended use case unambiguous.

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