list_content_spacesList the ProductClank content spaces you can draft into — spaces the user owns, delegates for, or manages that have their content engine turned on. Returns { space_id, name }. Call this first to resolve the space_id for write_content_candidates, and confirm the target space with the user.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds valuable behavioral context: it lists only spaces with content engine enabled, owned/delegated/managed by the user, and the specific return schema. This goes beyond annotations, and there is no contradiction.
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 two sentences with no wasted words. It front-loads the purpose and provides actionable guidance in a compact format. Every sentence earns its place.
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 simplicity (no parameters, no output schema), the description covers everything needed: purpose, eligibility criteria, return fields, and usage sequencing. It tells the agent to resolve the space_id for a sibling tool and confirm with the user, which is complete for this listing operation.
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 tool has zero parameters, so there is no need for the description to add parameter meaning. The input schema is empty, and schema description coverage is 100% by default. The description does not add parameter info (not needed), but it does clarify the output structure. A score of 4 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 verb 'List', the resource 'ProductClank content spaces you can draft into', and includes specific constraints (user ownership/delegation/management, content engine turned on). It also mentions the return fields { space_id, name }, making the purpose unambiguous and distinct from sibling tools like write_content_candidates or boost_post.
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 advises to 'Call this first to resolve the space_id for write_content_candidates, and confirm the target space with the user.' This tells the agent exactly when to use this tool (as a prerequisite for write_content_candidates) and includes a user confirmation step, providing strong usage guidance.
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.