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engram

engram

by TushaeBXN
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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engram_kg_query

Query a temporal knowledge graph to recall stored facts and relationships for an entity, optionally filtered by predicate and active status.

Instructions

Query the temporal knowledge graph for an entity.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entity": "<entity>"
    },
    "name": "engram_kg_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
entityYes
predicateNo
active_onlyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.7.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It says nothing about whether the query returns only current facts versus historical/superseded ones, how the temporal aspect is surfaced, or how results are ordered or paginated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no padding, which is structurally efficient. However, it is under-specified rather than genuinely concise, leaving room for detail it omits.

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?

With no annotations, no output schema, and three parameters at 0% schema coverage, the definition is too thin for the tool's complexity. It omits return shape and the temporal/active-fact semantics an agent would need to call it correctly.

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?

Schema description coverage is 0%, so the description must compensate but only covers the 'entity' parameter implicitly. The 'predicate' filter and especially 'active_only' (default true, implying inclusion of invalidated/superseded facts when false) are left entirely unexplained.

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?

States a specific verb (Query) and resource (temporal knowledge graph) scoped to an entity, which is clearer than a bare name restatement. It does not explicitly distinguish itself from the KG siblings (engram_kg_add, engram_kg_invalidate, engram_kg_timeline), though the read-oriented verb implicitly separates it.

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 on when to prefer this over engram_kg_timeline or engram_search, and no mention of prerequisites or exclusions. The agent must infer usage purely from the name and description.

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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