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store_memory

Store structured codebase memories—patterns, conventions, decisions—to persist across sessions using SQLite.

Instructions

Store a structured memory for the current project. Use this when you discover important codebase patterns, conventions, decisions, or architecture details that should persist across sessions. Memories are stored in SQLite and survive restarts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceNoMemory group (default: "codebase"). Use "codebase" for coding memories.codebase
memoryTypeYesMemory kind: "map" (file tree, architecture), "convention" (coding rules, patterns), "decision" (technical choices + rationale), "snapshot" (current focus/blockers, use with ttlHours), "dependency" (key packages), "error_pattern" (recurring fixes)
keyYesUnique identifier within namespace+type (e.g., "file-tree", "naming-convention", "chose-sqlite-over-postgres")
valueYesThe memory content — structured JSON preferred (e.g., {"pattern": "camelCase", "scope": "variables"})
priorityNoInjection priority 1-10 (10 = always inject, 5 = default, 1 = low priority)
confidenceNoConfidence 0.0-1.0 (1.0 = certain, lower = inferred)
ttlHoursNoAuto-expire after N hours (use for snapshots/focus, omit for permanent memories)
projectIdNoProject ID (defaults to current project)
Behavior3/5

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

Discloses that memories are stored in SQLite and survive restarts. However, does not mention overwrite behavior, limits, or side effects beyond persistence. With no annotations, additional detail would be beneficial.

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, no filler. First sentence states purpose, second adds usage guidance. Every word earns its place.

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

Completeness4/5

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

For an 8-parameter tool with no output schema, the description covers core purpose and storage behavior. Could mention conflict handling or return value expectations, but overall adequate.

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 coverage is 100% with good parameter descriptions. The tool description adds no extra param info beyond what is in the schema, which is acceptable but does not elevate the score.

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 uses a specific verb 'Store' and resource 'structured memory' for the current project, and distinguishes it by stating it persists across sessions. Sibling tools like recall_memory and delete_memory are clearly different operations.

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 states when to use: 'when you discover important codebase patterns, conventions, decisions, or architecture details that should persist across sessions.' Does not explicitly exclude alternatives, but the context makes it clear this is the only store tool.

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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