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save_memory

Record facts, preferences, decisions, and architecture details to persist across all Claude Code sessions for future reference.

Instructions

Store a developer memory (fact, preference, decision, architecture detail). Memories persist across all Claude Code sessions and are available in future conversations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe fact to remember (complete sentence)
memory_typeNoType: identity, preference, architecture, decision, bug, dependency, pattern, context. Custom types also accepted for non-developer domains.context
categoryNoCategory: frontend, backend, database, devops, testing, security, performance, tooling, api, general. Custom categories also accepted for non-developer domains.general
subjectNoWhat this is about, e.g. "auth_system", "react_version", "tab_width"
importanceNo1-10 (10 = core architecture, 1 = trivial)
scopeNoglobal = applies everywhere, project = specific to this codebase, team = shared with team membersproject
team_idNoTeam ID (required when scope is "team"). The memory will be shared with all team members.
tagsNoOptional tags for grouping/threading memories (max 5 tags, each max 30 chars). E.g., ["marketing-campaign", "feb-2026"]
ttlNoSet an expiration time. Use for temporary context like current task status. Format: "24h", "7d", "30d". Memory auto-archives after expiry.
project_idNoProject identifier override (auto-detected from CLAUDE_PROJECT_DIR or git remote if omitted)
Behavior3/5

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

With no annotations, the description carries full burden. It discloses that memories persist across sessions, a key behavioral trait. However, it does not mention idempotency, side effects, authorization needs, or rate limits.

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?

The description is two sentences long with no superfluous words. It efficiently conveys the core purpose and persistence behavior.

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

Completeness3/5

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

Given 10 parameters fully described in schema, the description covers the main purpose. However, it omits what the tool returns (e.g., memory ID) and does not mention auto-detection of project_id even though that is in the parameter schema.

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 the schema already documents all parameters. The tool description adds no additional parameter meaning beyond what is in the schema.

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 stores developer memories like facts, preferences, decisions, and architecture details. It uses specific verbs and resources, but does not explicitly differentiate from siblings like update_memory or recall_memories.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as update_memory, delete_memory, or recall_memories. The description lacks context on prerequisites or selection criteria.

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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