GoodMemory

goodmemory_get_context

Fetch a compact memory context for any workspace question when current context is insufficient or you need recall for a different query. Get relevant stored memory to answer accurately.

Instructions

Fetch a compact memory context fragment for a specific question about this workspace. Call it when hook-injected context is missing or insufficient, or when you need memory for a different question than the current prompt.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "goodmemory_get_context"
  }
}

Input Schema

Name	Required	Description
`cwd`	No	Workspace root. Defaults to the current working directory.
`query`	Yes
`output`	No
`maxTokens`	No
`sessionId`	No	Optional host session id for session-scoped recall.
`retrievalProfile`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.5.1Jul 13, 2026

TDQS

B3.4/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral traits. It only mentions 'compact memory context fragment' without disclosing any side effects, performance implications, authentication requirements, or limitations. The description lacks transparency about what the tool actually does beyond returning a fragment.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first defines purpose, second provides usage guidelines. No fluff, efficient, and front-loaded with the core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 6 parameters, no output schema, and low schema coverage, the description is too minimal. It does not explain the output format or behavior beyond 'compact fragment', leaving the agent guessing about critical aspects like output encoding, token limits, or how sessionId affects retrieval.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is low (33%), yet the description only addresses the 'query' parameter (implied by 'specific question'). Other parameters like cwd, output, maxTokens, sessionId, and retrievalProfile are completely ignored. The description fails to compensate for the undocumented parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches a compact memory context fragment for a specific question about the workspace. The verb 'fetch' and resource 'memory context fragment' are specific and actionable, though it does not explicitly differentiate from sibling tools like goodmemory_get_records.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use scenarios: 'when hook-injected context is missing or insufficient' and 'when you need memory for a different question than the current prompt'. This gives clear guidance on appropriate usage contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server