Get topic details
get_topicGet one current Topic with its recent context.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| topicId | Yes | Topic ID from list_topics |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | Yes |
get_topicGet one current Topic with its recent context.
| Name | Required | Description | Default |
|---|---|---|---|
| topicId | Yes | Topic ID from list_topics |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / properties / data / properties / emergenceRemoved value: -{
- "type": "number"
-}Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / properties / data / properties / report / anyOfPrevious value: -[
- {
- "additionalProperties": false,
- "properties": {
- "id": {
- "type": "string"
- },
- "publishedAt": {
- "type": "string"
- },
- "title": {
- "type": "string"
- }
- },
- "required": [
- "id",
- "title",
- "publishedAt"
- ],
- "type": "object"
- },
- {
- "type": "null"
- }
-]New value: +[
+ {
+ "additionalProperties": false,
+ "properties": {
+ "id": {
+ "type": "string"
+ },
+ "publishedAt": {
+ "type": "string"
+ },
+ "revisedAt": {
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ]
+ },
+ "title": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "id",
+ "title",
+ "publishedAt",
+ "revisedAt"
+ ],
+ "type": "object"
+ },
+ {
+ "type": "null"
+ }
+]Output schema / properties / data / properties / emergenceAdded value: +{
+ "type": "number"
+}Output schema / properties / data / requiredPrevious value: -[
- "id",
- "rank",
- "name",
- "summary",
- "trend",
- "postCount",
- "authorCount",
- "lastSeenAt"
-]New value: +[
+ "id",
+ "rank",
+ "name",
+ "summary",
+ "postCount",
+ "authorCount",
+ "lastSeenAt"
+]Input schema / properties / topicId / descriptionPrevious value: -"Topic id from list_topics"New value: +"Topic ID from list_topics"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the agent knows this is a safe read operation with bounded context. The description adds 'with its recent context,' which hints at temporal scoping, but does not elaborate on the behavior (e.g., how 'recent' is defined, or whether the topic is updated). No contradiction with 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?
The description is a single, concise sentence that front-loads the core action. It is appropriately sized for a tool with one parameter and clear purpose, though it could be slightly more specific without bloat.
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 (single parameter, clear schema, annotations for safety, and an output schema present), the description is adequate. It explains the core function and the 'recent context' aspect. The output schema exists, so return value details are not needed.
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% (the only parameter topicId has a pattern and description referencing list_topics). The description does not add any new meaning beyond the schema, so 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 'Get one current Topic with its recent context.' This clearly identifies the verb (Get), the resource (Topic), and distinguishes it from siblings like get_report or list_topics. The mention of 'recent context' adds specificity, but the scope is not fully elaborated (e.g., what constitutes 'context').
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 implies that this tool is for retrieving a single topic, contrasting with list_topics (which likely returns many). However, there is no explicit guidance on when to use this tool versus siblings like get_topic_series or get_intel, nor any mention of prerequisites (e.g., topicId from list_topics is already in the schema).
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.
Each tool targets a distinct entity or action: single vs. list (get vs. list), intel vs. project vs. topic vs. report vs. cluster vs. vocabulary vs. credential check. No two tools have overlapping purposes; the descriptions clearly differentiate them.
Uses a consistent pattern: get_ for singular retrieval, list_ for plural searches/listing. Only 'me' deviates, but it's a standard name for credential checks. The pattern is predictable and easy to follow.
12 tools cover a focused domain (crypto intelligence) without unnecessary bloat. Each tool earns its place: core entities (projects, topics, intel), plus series, reports, vocabulary, clusters, and auth check. The count feels well-scoped.
The server provides a complete read surface for its domain: listing, searching, getting details, historical series, reports, and filter metadata. No obvious gaps for consuming intelligence (CRUD not expected in a read-only API).