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ContextLayer

by io.github.DotNova
OverviewDiscussionsAdmin

get_context

Get intelligent context from the knowledge graph. Pass a query describing what you need — the system will automatically route to the right data sources (tasks, sessions, documents, teams, blocks) based on intent analysis + graph traversal + semantic similarity. Optionally narrow scope with project name or session ID.

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": {
      "query": "<query>"
    },
    "name": "get_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesThe user's question or intent — used for intelligent context routing. Describe what context is needed.
max_tokensNoMaximum tokens for the response (default 500)
project_idNoProject ID (optional — if omitted, returns across all projects)
session_idNoSession ID (optional — if omitted, returns user-level context)
project_nameNoProject name (optional, alternative to project_id)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Although no annotations are provided, the description discloses key behaviors: intent analysis, graph traversal, semantic similarity, and automatic routing to multiple data sources. It does not describe output format or error handling, but as a retrieval tool the internal mechanism is well explained.

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 front-loaded, stating the primary purpose first and then the routing mechanism. The optional scope sentence is additional but relevant. No fluff 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 provides a solid overview of how the tool works and what it considers, which is sufficient for most use cases. It does not describe the exact return format, but with no output schema, this is a minor gap. The complexity of the knowledge graph is well addressed.

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?

The schema provides 100% coverage with detailed descriptions for all five parameters, so the baseline is 3. The description adds only a minor note about optionally narrowing scope, which is already reflected in the schema's optional flags and descriptions.

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 states the tool's function: 'Get intelligent context from the knowledge graph' with a specific verb and resource. It also distinguishes itself from siblings like get_context_routing by explaining the automatic routing mechanism and the data sources involved.

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?

The description gives clear usage context: pass a query and the system routes automatically. It mentions optional narrowing by project name or session ID, which guides when to use scope parameters. However, it does not explicitly state when not to use this tool or alternative tools.

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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