get_contextRetrieve compact local memory context for a task or question using namespace, tags, and query filters to surface relevant memories and conclusions.
Return compact local memory context for a task or question.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | ||
| tags | No | ||
| limit | No | ||
| query | No | Task or question to retrieve context for. | |
| namespace | No |
Changes observed during successful MCP inspections.
v0.1.7Input schema / properties / kindAdded value: +{
+ "enum": [
+ "memory",
+ "conclusion"
+ ],
+ "type": "string"
+}Input schema / properties / namespaceAdded value: +{
+ "minLength": 1,
+ "type": "string"
+}Input schema / properties / tagsAdded value: +{
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+}v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds the notion of 'compact' and 'local' context, which gives some behavioral color, but it does not disclose output format, filtering behavior, or namespace semantics.
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, front-loaded sentence with no filler. It is concise, but it is arguably too terse to carry the semantic weight needed for a tool with five parameters and many siblings.
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 number of parameters, the lack of an output schema, and the large sibling set, this description is incomplete. It does not explain parameter semantics, usage context, or what 'compact context' actually contains, so an agent would struggle to invoke it correctly.
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 only 20%, with only 'query' described. The description's 'task or question' maps to the query parameter, but it does not explain 'kind', 'tags', 'limit', or 'namespace'. With five parameters and low schema coverage, the description fails to compensate.
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 uses a specific verb ('Return') and resource ('compact local memory context'), and ties it to a task or question. However, it does not differentiate this tool from siblings like search_memory, recall_memory, or ask_memory, so it stops short of a 5.
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?
There is no guidance on when to use this tool versus the many sibling memory tools. No alternatives, exclusions, or contextual triggers are mentioned, leaving the agent to infer when get_context is the right choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.