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deepak-bhardwaj-ps

Smriti MCP

record_trace

Record an append-only memory trace to preserve raw observations from AI agents for later consolidation into durable memories.

Instructions

Record an append-only memory trace for shared agent experience. Traces are raw observations that agents can later consolidate into durable memories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesRaw trace content or observation to preserve.
typeNoTrace event type such as observed, recalled, remembered, or consolidated.observed
agentNoAgent identity writing the trace, for example codex or claude.
scopeNoStructured scope for the trace, such as project or repository.
memory_idNoRelated memory id, if this trace concerns an existing memory.
salienceNoOptional importance from 0 to 1.
metadataNoAdditional structured trace metadata.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the key behavior 'append-only', but does not mention authorization, rate limits, or other side effects. The behavior is partially transparent.

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, front-loaded with verb and resource, and no wasted words. Efficiently communicates the essence.

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?

Has an output schema, so return values are covered. Parameter schema is fully described. The description is concise but could mention persistence or limits; however, given the schema richness, it is reasonably complete.

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 description adds no additional parameter meaning beyond what the schema provides, meeting the baseline expectation.

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 identifies the tool's verb ('record') and resource ('memory trace'), and distinguishes it from sibling tools like 'create_memory' or 'append_memory' by emphasizing it is 'append-only' and for 'raw observations' that later consolidate into durable memories.

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 for raw observations but does not explicitly state when to use versus alternatives like 'create_memory' or 'append_memory'. It lacks direct guidance on when not to use this 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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