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sassy_memory_remember

Save structured memories that persist across sessions using key-value pairs, tags, priority levels, and project context. Ensure important information is never lost between conversations.

Instructions

Store a memory that persists across sessions.

key: unique identifier (use naming convention: task_state, pattern, blocker, decision) value: the memory content (what happened, what was learned, current state) tags: comma-separated (e.g. "task-active,tls,security") priority: critical | high | normal | low project: project name (e.g. "sassymcp", "sassy-browser")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
tagsNo
valueYes
projectNo
priorityNonormal

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description must carry the burden of behavioral disclosure. It mentions persistence across sessions, which is useful, but omits important behavioral traits such as what happens when an existing key is reused (overwrite vs. error), whether the operation is reversible, or any side effects. This is a significant gap for a write operation.

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 concise and well-structured: a single opening sentence followed by a clear parameter breakdown. Every line provides necessary information, with no filler or repetition.

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?

The description gives a complete picture for a simple memory-store tool: purpose, parameter semantics, and the key behavioral fact of persistence. An output schema is present, so return values need no explanation. It loses a point for not addressing the overwrite/update semantics, which is a common usage concern for persistent stores.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by explaining all five parameters: the key naming convention (task_<concept>_..., pattern_..., etc.), value content, comma-separated tags, priority levels (critical|high|normal|low), and project examples. This goes far beyond what the raw schema provides.

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 opens with 'Store a memory that persists across sessions,' using a specific verb ('store') and resource ('memory'). This clearly differentiates from sibling tools like sassy_memory_recall (retrieval) and sassy_memory_forget (deletion).

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

Usage Guidelines3/5

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

The description implies usage by stating the tool stores persistent memories and then details parameter conventions. However, it does not explicitly state when to use this tool versus alternatives (e.g., recall/search) or mention exclusions, so the guidance is more implicit than explicit.

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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