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total-agent-memory

total-agent-memory

by vbcherepanov
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Python
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memory_eval_temporal

Read-onlyIdempotent

Evaluate temporal recall using knowledge graph and filter, returning not-implemented status when modules are missing.

Instructions

v11.0 Phase 8: temporal recall using temporal_kg + temporal_filter. Returns {status: 'not_implemented', ...} when modules are missing.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "memory_eval_temporal"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeNofast
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior3/5

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

The description discloses that it returns a 'not_implemented' status when modules are missing, which is a useful behavioral detail. However, it does not describe any other side effects, return formats, or error conditions beyond that, and the read-only and idempotent annotations already cover safety.

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 a single sentence that directly states the purpose and a key behavior. It is concise and avoids unnecessary fluff, though it does include version and phase information that might be considered extraneous.

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

Completeness2/5

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

Given the simple schema and lack of output schema, the description provides minimal context. It does not explain what the tool actually returns (beyond the not_implemented case), how mode or limit influence results, or what temporal recall entails. This leaves significant gaps for an agent trying to decide whether to invoke it.

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

Parameters2/5

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

The input schema defines 'mode' with an enum and a default, and 'limit' as an integer, but the description does not explain their meanings or how they affect the operation. The enum values are self-explanatory to some degree, but 'limit' is left completely undefined.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it performs 'temporal recall using temporal_kg + temporal_filter', which gives a general sense of the operation, but the verb 'temporal recall' is vague and it does not clearly distinguish from sibling memory_eval_* tools. It also mentions a version and phase, which adds context but not clarity.

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 explicit guidance is provided on when to use this tool versus alternatives. The mention of 'Phase 8' hints at a workflow, but there is no direct comparison to other memory_eval_* tools or any clear usage conditions.

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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