suggest_topicSuggest an article title or topic. If a published article is a close match, the reply links it and asks what it does not answer; send that as explainer to queue the topic. [sign-in required]
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| sources | No | ||
| summary | No | ||
| explainer | No |
| Name | Required | Description | Default |
|---|---|---|---|
| gate | No | ||
| queued | No | ||
| status | No | ||
| message | Yes | ||
| published | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "gate": {
+ "type": "object"
+ },
+ "message": {
+ "type": "string"
+ },
+ "published": {
+ "type": "boolean"
+ },
+ "queued": {
+ "type": "boolean"
+ },
+ "status": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "published",
+ "message"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the mutation/non-idempotent/non-destructive profile, so the bar is lower; the description adds real context beyond them by flagging '[sign-in required]' and describing the two-step behavior (link a matching article, ask what it doesn't answer, then queue via explainer). It still omits what a repeat submission does, but that is minor against the annotation coverage.
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?
Three tight sentences, front-loaded with the purpose and then the conditional flow; no filler or repetition.
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?
An output schema exists so return values needn't be described, and the interaction flow plus auth note are covered. However, with 0% schema coverage and four parameters, the missing semantics for sources and summary leave the definition incomplete for a mutation 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?
Schema coverage is 0%, so the description carries the full burden. It only gives meaning to one parameter ('explainer' queues the topic) while title, sources, and summary receive no explanation at all, leaving three of four parameters undocumented.
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?
States a specific verb and resource: 'Suggest an article title or topic.' An agent can distinguish it from write-oriented siblings like propose_new_article or suggest_article_change, though the description never names those siblings explicitly.
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?
It implies a workflow ('if a published article is a close match... send that as explainer to queue the topic') but gives no explicit when-to-use vs when-not guidance and never contrasts with the many sibling tools for articles and suggestions. Usage is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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