tentra

get_service_code_graph

Retrieve the complete code subgraph for a Tentra canvas service, including files, symbols, and cross-service dependencies, to analyze code relationships and architecture.

Instructions

Returns the full code subgraph for a Tentra canvas service: files, symbols, and cross-service edges.

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": {
      "service_id": "<service_id>",
      "snapshot_id": "<snapshot_id>"
    },
    "name": "get_service_code_graph"
  }
}

Input Schema

Name	Required	Description
`service_id`	Yes	Tentra canvas service ID
`snapshot_id`	Yes	Snapshot to query
`depth`	No	Edge traversal depth for cross-service edges
`include_semantics`	No	Include AI-extracted purpose + domain tags per symbol

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Apr 18, 2026

TDQS

B3.2/5.0

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 burden. It mentions the return content but lacks details on behavioral traits like rate limits, authentication needs, response format, pagination, or error handling. The description is minimal and doesn't compensate for the absence of annotations.

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 a single, efficient sentence with zero waste. It is front-loaded, directly stating the tool's purpose without unnecessary details, making it easy to parse quickly.

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 complexity of a 4-parameter tool with no annotations and no output schema, the description is incomplete. It doesn't explain the return values, error cases, or usage context, leaving significant gaps for an AI agent to understand how to invoke and interpret results effectively.

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 fully documents all parameters. The description adds no additional meaning beyond what's in the schema, such as explaining the significance of 'depth' or 'include_semantics' in context. Baseline 3 is appropriate since the schema does the heavy lifting.

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 verb ('Returns') and resource ('full code subgraph for a Tentra canvas service'), specifying what it returns ('files, symbols, and cross-service edges'). It distinguishes from siblings like 'get_architecture' or 'get_symbol_neighbors' by focusing on the complete subgraph with cross-service edges.

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 is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, such as when to choose 'get_architecture' for structural overview or 'query_symbols' for specific symbols instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.