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refactor: remove legacy ktx compatibility shims (#211)

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* refactor: remove legacy ktx compatibility shims

* fix: restore overlay collision guidance
This commit is contained in:
Andrey Avtomonov 2026-05-24 16:57:23 +02:00 • committed by GitHub
parent a954a29a76
commit 96952fb43c
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59 changed files with 294 additions and 342 deletions
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63
packages/cli/src/context/mcp/context-tools.ts
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@ -54,13 +54,13 @@ const toolDescriptions = {
'Search KTX wiki pages for reusable business context. Example: wiki_search({ query: "revenue recognition", limit: 5 }).',
wiki_read: 'Read a KTX wiki page by key returned from wiki_search. Example: wiki_read({ key: "global/revenue" }).',
entity_details:
'Read table and column metadata from the latest live-database scan snapshot. Example: entity_details({ connectionId: "warehouse", entities: [{ table: { schema: "public", table: "orders" }, columns: ["id"] }] }).',
'Read table and column metadata from the latest live-database scan snapshot. Example: entity_details({ connectionId: "warehouse", entities: [{ table: { catalog: null, db: "public", name: "orders" }, columns: ["id"] }] }).',
dictionary_search:
'Search profile-sampled warehouse values to locate likely source columns for business values. Example: dictionary_search({ values: ["Acme Corp"], connectionId: "warehouse" }).',
sl_read_source:
'Read a semantic-layer YAML source by connection id and source name. Example: sl_read_source({ connectionId: "warehouse", sourceName: "orders" }).',
sl_query:
'Execute a semantic-layer query and return rows, headers, generated SQL, and plan details. Example: sl_query({ connectionId: "warehouse", measures: ["orders.order_count"], dimensions: [{ dimension: "orders.created_at", granularity: "month" }] }).',
'Execute a semantic-layer query and return rows, headers, generated SQL, and plan details. Example: sl_query({ connectionId: "warehouse", measures: ["orders.order_count"], dimensions: [{ field: "orders.created_at", granularity: "month" }] }).',
sql_execution:
'Execute one parser-validated read-only SQL query against a configured KTX connection. Example: sql_execution({ connectionId: "warehouse", sql: "select count(*) from public.orders", maxRows: 100 }).',
memory_ingest:
@ -93,44 +93,16 @@ const slQueryMeasureSchema = z.union([
}),
]);
const slQueryDimensionSchema = z.preprocess(
(value) => {
if (typeof value === 'string') return { field: value };
if (value && typeof value === 'object' && !Array.isArray(value)) {
const obj = { ...(value as Record<string, unknown>) };
if (!('field' in obj) && typeof obj.dimension === 'string') obj.field = obj.dimension;
return obj;
}
return value;
},
z.object({
const slQueryDimensionSchema = z.object({
field: z.string().min(1).describe('Dimension to group by, e.g. "orders.created_at" or "orders.status".'),
granularity: z
.string()
.min(1)
.optional()
.describe('Time grain for time dimensions: day, week, month, quarter, or year.'),
}),
);
});
const slQueryOrderBySchema = z.preprocess(
(value) => {
if (typeof value === 'string') {
return { field: value };
}
if (value && typeof value === 'object' && !Array.isArray(value)) {
const obj = { ...(value as Record<string, unknown>) };
if (!('field' in obj) && typeof obj.id === 'string') {
obj.field = obj.id;
}
if (!('direction' in obj) && 'desc' in obj) {
obj.direction = obj.desc === true ? 'desc' : 'asc';
}
return obj;
}
return value;
},
z.object({
const slQueryOrderBySchema = z.object({
field: z
.string()
.min(1)
@ -141,8 +113,7 @@ const slQueryOrderBySchema = z.preprocess(
.enum(['asc', 'desc'])
.default('asc')
.describe('Sort direction: "asc" or "desc". Defaults to "asc".'),
}),
);
});
const slQuerySchema = z.object({
connectionId: connectionIdSchema
@ -152,7 +123,7 @@ const slQuerySchema = z.object({
dimensions: z
.array(slQueryDimensionSchema)
.default([])
.describe('Dimensions to group by. Strings and {dimension, granularity} are accepted.'),
.describe('Dimensions to group by. Use {field, granularity?} entries.'),
filters: z
.array(z.string().describe('Semantic-layer filter expression, e.g. "orders.status = paid".'))
.default([])
@ -164,28 +135,16 @@ const slQuerySchema = z.object({
order_by: z
.array(slQueryOrderBySchema)
.default([])
.describe('Sort clauses. Strings and Cube-style {id, desc} are accepted.'),
.describe('Sort clauses. Use {field, direction?} entries.'),
limit: z.number().int().min(0).default(1000).describe('Maximum rows to return. Defaults to 1000.'),
include_empty: z.boolean().default(true).describe('Whether to include empty dimension groups. Defaults to true.'),
});
const entityDetailsTableRefSchema = z.preprocess(
(value) => {
if (value && typeof value === 'object' && !Array.isArray(value)) {
const obj = { ...(value as Record<string, unknown>) };
if (!('db' in obj) && typeof obj.schema === 'string') obj.db = obj.schema;
if (!('name' in obj) && typeof obj.table === 'string') obj.name = obj.table;
if (!('catalog' in obj)) obj.catalog = null;
return obj;
}
return value;
},
z.object({
const entityDetailsTableRefSchema = z.object({
catalog: z.string().nullable().describe('Catalog/project/database. Use null when not applicable.'),
db: z.string().nullable().describe('Schema/database/dataset. Use null when not applicable.'),
name: z.string().min(1).describe('Table name.'),
}),
);
});
const entityDetailsSchema = z.object({
connectionId: connectionIdSchema.describe('Connection id whose latest scan snapshot should be read.'),
@ -194,7 +153,7 @@ const entityDetailsSchema = z.object({
z.object({
table: z
.union([z.string().min(1), entityDetailsTableRefSchema])
.describe('Table display string or object ref. {schema, table} is accepted as an alias for {db, name}.'),
.describe('Table display string or canonical object ref.'),
columns: z
.array(z.string().min(1).describe('Column name to inspect.'))
.optional()