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Use when the user needs vector search, semantic similarity, HNSW index, or graph queries on IRIS data
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use when creating or modifying InterSystems IRIS interoperability production components in Python — Business Services, Business Processes, Business Operations, Adapters, Messages, or Production definitions.
Measure ObjectScript line coverage using %Monitor.System.LineByLine. Wraps a %UnitTest.Manager.RunTest() call, collects per-class hit/total counts, prints a coverage table. Prerequisite: iris-coverage-setup (bbsiz=4096, IRIS restarted).
Measure ObjectScript line coverage using iris_coverage. Use when a user asks about test coverage, coverage reports, or wants to know how well their test suite exercises their code.
InterSystems AI Hub EAP (Early Access Program) — accurate API patterns for builds 158/159/161/162 (current). Covers %AI.Agent declarative Parameters, %AI.Provider.Create, ConfigStore/GetProviderForConfig, @{env/config/wallet} substitution, session management, streaming, tool sets, and known breaking changes from build 141. Load when helping EAP participants set up, build, or debug AI Hub projects.
Use after writing or editing any ObjectScript .cls file, after applying a fix to a compile error, or before declaring a task done — uploads the class to IRIS via Atelier REST, compiles it, and returns structured errors for immediate fixing.
Manage and observe IRIS Interoperability productions — lifecycle, logs, queues, and message tracing
| name | iris-vector-graph |
| description | Use when the user needs vector search, semantic similarity, HNSW index, or graph queries on IRIS data |
| managed_by | iris-agentic-dev |
Project: iris-vector-graph
Install: zpm "install iris-vector-graph"
Requires: IRIS 2024.1+; ZPM package manager
iris-vector-graph adds vector search and graph traversal capabilities to IRIS:
SELECT TOP 10 ... ORDER BY VECTOR_DOT_PRODUCT(embedding, :query_vec) syntax-- Create a table with a vector column
CREATE TABLE documents (
id INT IDENTITY,
content VARCHAR(2000),
embedding VECTOR(FLOAT, 1536)
)
-- Insert a document with its embedding
INSERT INTO documents (content, embedding)
VALUES ('InterSystems IRIS overview', TO_VECTOR('[0.1, 0.2, ...]', FLOAT, 1536))
-- Nearest-neighbor search
SELECT TOP 5 id, content,
VECTOR_DOT_PRODUCT(embedding, TO_VECTOR(:query_embedding, FLOAT, 1536)) AS score
FROM documents
ORDER BY score DESC
# From an IRIS terminal or via iris-agentic-dev
zpm "install iris-vector-graph"
Or in module.xml:
<Dependency>
<ModuleName>iris-vector-graph</ModuleName>
<Version>*</Version>
</Dependency>
| Class | Purpose |
|---|---|
community.vectorgraph.VectorIndex | Manage HNSW index lifecycle |
community.vectorgraph.Search | Run similarity queries |
community.vectorgraph.Graph | Edge storage and traversal |