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get_user_context

Read-onlyIdempotent

Retrieve the current user's cognitive identity and active session context, including role, expertise, project focus, and recent memory themes, to personalize AI responses without re-explanation.

Instructions

Get the current user's cognitive identity and active session context.

Call this at the START of a conversation to understand who you're talking to — their role, expertise, current project, and recent memory themes.

This is the core of Purmemo's identity layer: once set in the dashboard, your identity travels silently to every AI session so you're never explaining yourself from scratch again.

WHAT IT RETURNS:

  • identity: role, expertise areas, primary domain, work style, preferred tools

  • current_session: what the user is working on right now (project, focus)

  • memory_summary: 2-3 sentence synthesis of the user's most recent memory themes

WHEN TO CALL:

  • At the start of every new session (add to Claude system prompt)

  • When user says "load my context" or "what do you know about me?"

  • Before making recommendations that depend on knowing the user's background

EXAMPLE USAGE: → User starts new Claude session → Claude calls get_user_context automatically → Response: { role: "founder", expertise: ["product", "fullstack"], project: "purmemo", focus: "identity layer", memory_summary: "Chris has been building Purmemo's..." } → Claude responds with full context already loaded — no re-explaining needed

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds value by explaining the return structure and the concept of the identity layer, without contradicting annotations.

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

Conciseness4/5

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

Well-structured with sections for purpose, returns, when to call, and example. Some marketing phrasing ('travels silently') could be trimmed, but overall concise and informative.

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

Completeness5/5

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

For a zero-parameter tool without output schema, the description fully explains what is returned, when to use, and includes an example response, making it complete for an agent to understand.

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

Parameters4/5

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

No parameters exist (schema coverage 100% with empty). Baseline 4 applies; description implies zero-argument invocation, which is sufficient.

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

Purpose5/5

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

The description clearly states it retrieves the user's cognitive identity and session context, with specific details on what it returns (identity, current session, memory summary). It distinguishes from siblings like get_public_memory or recall_memories by focusing on user context.

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

Usage Guidelines4/5

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

Explicitly recommends calling at the start of every conversation and before background-dependent recommendations. Also handles user queries like 'load my context'. Could explicitly mention when NOT to use, but it's clear from context.

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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