Skip to main content
Glama
nstok-id

NSTOK AI Software Factory MCP Server

Official
by nstok-id

update_knowledge

Store newly generated application or feature metadata into Nstok-knowledge-master so agents can discover and reuse assets. Capture IDs, types, and relationships to keep the knowledge graph current.

Instructions

Feed newly generated application or feature metadata back into Nstok-knowledge-master.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUnique identifier of the newly created entity (e.g. "sales-report", "Nstok-app-w")
nameYesHuman readable name of the asset
typeYesAsset type
dbEntitiesNoDB entities used by this asset
repositoryYesRepository containing the asset
descriptionYesOverview of what the asset does
capabilitiesNoList of capabilities provided
dependenciesNoDependencies used by this asset
uiComponentsNoUI components used by this asset
relationshipsNoGraph relationships to link

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden and falls short. It never states whether this creates or overwrites an existing knowledge entry, whether it is idempotent on a repeated id, what permissions are needed, or what side effects graph relationships have. The name says "update" while the body says "feed newly generated ... metadata," leaving the create-vs-upsert semantics ambiguous.

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?

It is a single sentence with no filler and the target system is front-loaded. It is efficient, though terse enough that the brevity edges toward under-specification rather than crispness.

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?

For a 10-parameter mutation tool with 5 required fields, an enum-typed relationship edge structure, no output schema, and no annotations, one sentence is not enough. Missing are the create-vs-upsert semantics, what the relationship types mean when linking assets, and what a successful call returns.

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 each of the 10 parameters is already documented in the schema, which sets the baseline at 3. The description adds nothing about parameters, not even the existence of the relationships or dbEntities graph fields.

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 gives a loose verb phrase ("Feed ... back into") and a named resource ("Nstok-knowledge-master"), so the agent can infer it writes metadata into a knowledge base. However, it understates the scope: the schema supports six asset types (feature, ui_component, db_entity, application, repository, pattern) plus relationship edges, while the description only mentions "application or feature metadata." It also doesn't distinguish this from siblings like create_app or create_feature.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as create_feature or add_feature_to_app, which mutate overlapping data. The single clause "newly generated" is the only usage cue and it is implicit at best.

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