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langchain-oracledb-helper

Scaffold a langchain-oracledb store layer — multi-collection OracleVS wrapper, metadata-as-string monkeypatch, embedder-dim assertion, OracleChatHistory subclass (langchain-oracledb does not ship one). Use when a project needs Oracle as its LangChain vector store and chat-history backend.

70

Quality

86%

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SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered, highly actionable scaffolding skill: a clear step sequence with validation, error-recovery loops, explicit stop conditions, and conditional one-level-deep references. The residual weaknesses are minor — some placeholder gaps in the store.py skeleton, a little duplicated warning text, and reliance on shared/ files that are not shipped inside this bundle.

Suggestions

Make the store.py skeleton fully executable by inlining the per-embedder import lines (or by giving one complete worked example per embedder choice) instead of leaving '# ... embedder import per choice ...' and '<collections list>' placeholders for the executor to stitch from other steps.

Deduplicate the monkeypatch warning — state it once (e.g., in 'What you must NOT do') and reference it from Step 3, and merge the two 'Oracle does NOT support CREATE TABLE IF NOT EXISTS' remarks into the Step 5 migration section.

Verify the shared/ references ship with (or resolve relative to) this skill, or list them in the bundle's references/ directory, so the deferred content the body depends on is actually discoverable where the paths point.

DimensionReasoningScore

Conciseness

The body is dense and almost entirely actionable — no generic library tutorials or concepts Claude already knows, and the rationale paragraphs ("The whole point of defaulting to..." , the ORA-43853/SYSTEM tablespace warning) are project-specific knowledge, not padding. It is not 5 because there is small duplication: the "don't skip _monkeypatch" warning appears in both Step 3 and 'What you must NOT do', and the "Oracle does NOT support CREATE TABLE IF NOT EXISTS" note appears twice (Step 0 and Step 5).

4 / 5

Actionability

Guidance is nearly copy-paste ready: exact env var names, a full executable PL/SQL DDL block, per-embedder factory expressions, a concrete smoke-test snippet, and explicit 'replace placeholders with concrete values from inputs' instructions. It stops short of anchor 5 because the store.py skeleton retains placeholder gaps ("# ... embedder import per choice ...", "<collections list>", "EXPECTED_DIM = <384 | 1024>") the executor must stitch together from other steps.

4 / 5

Workflow Clarity

A clear Step 0–6 sequence with explicit validation checkpoints and feedback loops appropriate to database work: input validation with hard stops (Step 1), an idempotent bootstrap, a smoke test with a dim assertion and a recovery loop (drop tables, fix embedder, re-bootstrap), plus dedicated 'Stop conditions' and 'What you must NOT do' sections. This matches the anchor 5 example's validate → fix → retry structure; there is no missing checkpoint.

5 / 5

Progressive Disclosure

References are one level deep, clearly signaled, and conditionally gated ("only if embedder == 'in-db-onnx'"), and SKILL.md stays an overview that defers bulk content (monkeypatch, chat history, in-DB embeddings) to snippet files rather than inlining it. It is not 5 because the shared/references and shared/snippets files are not present in this skill's bundle to verify, and the body still inlines a sizeable code skeleton and full DDL that could arguably live in the referenced files.

4 / 5

Total

17

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20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: specific, third-person, with an explicit 'Use when...' trigger clause and a well-delineated niche. The only weakness is modest keyword breadth — a few natural synonyms (Oracle 23ai, AI Vector Search, OCI) that users might say are absent.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "multi-collection OracleVS wrapper, metadata-as-string monkeypatch, embedder-dim assertion, OracleChatHistory subclass" — with specifics Claude could not infer ("langchain-oracledb does not ship one"). This matches the anchor for comprehensive coverage of specific concrete actions; it is not score 4 because there are no notable coverage gaps in what the skill does.

5 / 5

Completeness

It explicitly answers both parts: the "what" is the scaffolded store layer with its four concrete deliverables, and the "when" is a concrete trigger phrase — "Use when a project needs Oracle as its LangChain vector store and chat-history backend". This mirrors the anchor 5 example's structure; it is not score 4 because the when-clause is fully explicit rather than merely present.

5 / 5

Trigger Term Quality

"Oracle", "LangChain", "vector store", and "chat-history backend" are natural phrases a user with this need would say, giving good keyword coverage. It falls short of the anchor 5 comprehensive-coverage example because common synonyms and variants ("Oracle Database 23ai", "AI Vector Search", "OCI", "RAG backend") are missing.

4 / 5

Distinctiveness Conflict Risk

"langchain-oracledb" and "OracleVS" pin a clear niche with distinct triggers; no plausible competing skill (generic Oracle SQL, other vector stores) would capture this query. Minimal conflict risk matches the anchor 5 'clear niche' example.

5 / 5

Total

19

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20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
oracle-devrel/oracle-ai-developer-hub
Reviewed

Table of Contents

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