search_productsSearch the user's ProductClank products by name and return their IDs. A product_id is required to create or boost a campaign — use this to resolve it, then confirm the match with the user.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 5) | |
| query | Yes | Product name or keyword to search for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so the description carries a lower burden. It adds that the tool returns IDs, but does not disclose behavior like partial matching, pagination, or case sensitivity. The description is consistent with annotations and adds some workflow context.
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 sentences, zero waste. The first sentence states the core action and output. The second sentence provides context and a workflow hint. Every sentence is essential.
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?
For a simple search tool with no output schema, the description is fairly complete. It explains the purpose, output, and why the tool is needed. It could be more explicit about matching behavior, but the combination with annotations and schema makes it adequate.
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 description coverage is 100% – both parameters have clear descriptions. The tool description only mentions 'by name' which maps to the query parameter, adding no new meaning beyond 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 states 'Search the user's ProductClank products by name and return their IDs' – a specific verb+resource with clear output. It distinguishes from siblings like create_product and list_content_spaces by focusing on search/lookup for campaign resolution.
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 explicitly ties this tool to campaign creation/boosting workflow: 'A product_id is required to create or boost a campaign — use this to resolve it, then confirm the match with the user.' It provides clear context for when to use, though it does not explicitly mention when not to use or name alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools map cleanly to a distinct resource and action: campaigns, posts, products, research, content spaces, and submissions. A few pairs are close—`create_campaign` vs `create_content_campaign` and `check_balance` vs `get_earnings`—but the detailed descriptions make the intended selection clear.
The set largely follows a consistent `verb_noun` snake_case pattern (`list_campaigns`, `generate_posts`, `update_campaign`, `submit_participation`). Minor deviations keep it from a perfect score: `credit_history` lacks a verb, and `create_campaign` reads as generic next to the more specific `create_content_campaign`.
30 tools is high and makes the server feel heavy, but the domain genuinely spans products, credits, campaigns, research, post discovery, content spaces, boosts, and participation rewards. The breadth mostly earns the count, though it sits on the wrong side of the typical 3–15 range.
The core end-to-end workflow is covered: create and configure campaigns, discover and refine posts, run research, find opportunities, submit work, and measure results. Gaps exist but are minor for the central purpose—product listings can’t be updated or deleted, and delegates can be added but not removed.