Content
88%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A strong, execution-focused skill: complete SQL for every step, a clear gated workflow with error-recovery feedback loops, and a sensible split of exhaustive parameter detail into a verified one-level-deep reference. The main improvement room is tightening the opener and moving more of the long privilege/execute-as-user reference material into separate files.
Suggestions
Trim the marketing-style opening line ('Snowflake Native App — graph algorithm power inside Snowflake') to a plain statement of what the skill does, and consolidate the repeated 're-run Step 2e caller grants' reminders into one place.
Move the execute-as-user privilege setup (Part B option 2, including rotation/rollback SQL) into a dedicated reference file (e.g. references/execute-as-user.md), keeping only the mode-selection table and a pointer in SKILL.md.
Consider moving the per-algorithm tables (procedure names and one-line use cases) into references/algorithms.md alongside the parameter tables, since the body already points there for algorithm detail.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and token-efficient — casting rules and troubleshooting are compacted into tables, and it never explains concepts Claude already knows (no 'what is PageRank' padding). Minor trimmable spots remain: the marketing-flavored opener ('graph algorithm power inside Snowflake') and some repetitive re-mentions of the caller-grant re-run rule. | 4 / 5 |
Actionability | Every step ships copy-paste-ready SQL: GET_DDL/INFORMATION_SCHEMA inspection, CREATE VIEW with explicit casts, a complete single-CALL example with full project/compute/write config, grant scripts for both auth modes, and a PAT mint/store/register/rotate sequence with the one-time token-secret warning. | 5 / 5 |
Workflow Clarity | The four-step flow (explore → prepare views → project-compute-write → inspect/join) is explicitly sequenced with a warning against skipping preparation, and validation is woven throughout: a STOP checkpoint for the one-time token secret, explicit user confirmation before slow GraphSAGE training, an error-message→fix troubleshooting table (feedback loops for a database-operation context), and a closing checklist including 'output table populated'. | 5 / 5 |
Progressive Disclosure | The exhaustive per-algorithm parameter reference is correctly offloaded to a real, clearly signaled one-level-deep file (references/algorithms.md), and the body keeps a compact summary. However, the body itself runs ~500 lines with large reference-style sections (the full execute-as-user setup, model catalog, algorithm tables) that could partly live in additional reference files. | 4 / 5 |
Total | 18 / 20 Passed |