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NSTOK AI Software Factory MCP Server

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get_feature_context

Retrieve deep-dive context for a feature by its ID, including capabilities, routes, UI/DB dependencies, and graph traversal.

Instructions

Get deep-dive context for a specific feature, including capabilities, routes, UI/DB deps, and graph traversal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
featureIdYesID of the feature (e.g. "inventory-management", "auth-management")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. 'Get' plus a list of read-oriented artifacts (capabilities, routes, deps) implies a safe read operation, and it discloses the breadth of content returned, but it says nothing about traversal depth, cost, or limits. Adequate but not rich.

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?

A single front-loaded sentence with no filler; the content list is the useful part. Slightly dense with jargon ('graph traversal') that could have been unpacked without lengthening the sentence much.

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?

There is no output schema, so the description must indicate what comes back, and it does list the artifact categories. What remains missing is how deep the traversal goes and what the agent should do with the result, but for a single-parameter retrieval tool this 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?

Only one parameter and schema description coverage is 100%, with concrete example IDs in the schema, so the baseline is 3. The description adds no format or constraint detail about featureId beyond what the schema already supplies.

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?

Specific verb+resource: 'Get deep-dive context for a specific feature,' and it enumerates the returned content (capabilities, routes, UI/DB deps, graph traversal). It is distinguishable from siblings like find_features or search_knowledge, though it never names them to reinforce the distinction.

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?

Usage is only implied by the phrase 'for a specific feature,' which suggests it is the second step after locating a feature ID. There is no explicit when-to-use, when-not-to-use, or pointer to an alternative sibling such as find_features for discovery or get_app_context for broader scope.

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