betterpost_suggest_topicsClusters a project's current stories into a few candidate angles — each with a label, how many stories back it, and example headlines — and warms the project (gathers and ranks fresh stories) in the process. Returns topics you can offer the user before generate_content.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | ||
| count | No | ||
| projectId | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| topics | Yes | ||
| projectId | Yes |
Changes observed during successful MCP inspections.
Input schema / properties / tokenRemoved value: -{
- "description": "Your saved BetterPost token from a prior call (demo `bp_demo_…` or paid `bp_live_…`). Reuse the same token on every call and across conversations; omit only on the very first call to be issued a free demo token. Paid users may instead pass the key in the server URL (?key=…) or an Authorization: Bearer header.",
- "type": "string"
-}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the side effect of 'warming' the project (gathering and ranking stories), consistent with readOnlyHint=false. Adds context beyond annotations.
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 concise sentences that front-load the main action. Could be slightly more structured but functional.
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?
Describes output (topics with label, stories back, headlines) but leaves parameter details and side-effect implications unexplained. Adequate given output schema exists.
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?
No parameter descriptions; 0% schema coverage. Does not explain type, count, or projectId meaning despite having 3 parameters with constraints.
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?
Description clearly states it clusters stories into candidate angles and prepares topics for generate_content. Distinguishes itself from sibling generate_content by indicating it should be used before.
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?
Implies use before generate_content but lacks explicit guidance on when not to use or alternatives among many siblings.
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.