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remember_context

Save context information like codebase overviews or project summaries to cache for later recall without re-computation. Overwrites existing entries under the same key.

Instructions

Save context information to the cache so you can recall it later without re-computing. Perfect for caching: codebase overviews, file summaries, project structure, frequently-accessed data, or "thinking" results like dependency analysis. The AI assistant can use this to avoid re-reading the entire codebase every time. Overwrites any existing value stored under the same key. Returns { key, stored_at, ttl } confirming the saved context. Example: remember_context("project overview", "This is a Next.js app with...") then later: recall_context("project overview"). Use recall_context to retrieve; use list_remembered to see all stored keys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_idYesUUID of the cache instance
keyYesDescriptive key like "project_overview", "auth_architecture", "file:src/index.ts"
contentYesThe context/summary/analysis to remember
categoryNoCategory for organization (default: custom)
ttlNoTime-to-live in seconds (default: 86400 = 24h, use 0 for no expiry)
Behavior4/5

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

With no annotations, the description carries full burden. It discloses overwrite behavior and return format, but omits additional context like concurrency or failure modes, though not critical for a cache tool.

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?

The description is well-structured and front-loaded, each sentence adds value, though slightly verbose. Could be trimmed without losing clarity.

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?

Given 5 params, no output schema, and no annotations, the description covers purpose, use cases, behavior, return format, example, and sibling references comprehensively.

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

Parameters3/5

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

Schema description coverage is 100%, so baseline is 3. The description adds a usage example but does not significantly elaborate beyond the schema's parameter descriptions.

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 the verb 'save' and resource 'context information to the cache', and explicitly mentions sibling tools recall_context and list_remembered, distinguishing its purpose.

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?

It provides explicit guidance on ideal use cases (codebase overviews, file summaries, etc.) and directs the agent to use recall_context for retrieval and list_remembered to see stored keys, effectively setting boundaries with siblings.

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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