Content
78%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 well-structured, directive-heavy skill body: concrete code for the main workflow, a clear 4-step sequence, and exemplary one-level-deep reference structure. The main gaps are a missing example for the mandated DynamoAccess module, no explicit error-recovery loop for deploy, and slight repetition of the generate-client prohibition.
Suggestions
Add a short code example for the required DynamoAccess module (common/dynamo_access.py with get_dynamo_access()), since Rule 6 and the project layout mandate it but the workflow never shows how to implement it.
Include an explicit validation/error-recovery checkpoint after the deploy step (e.g., what to do when `easysam generate` reports schema validation errors: fix models.py and re-run) to close the feedback loop for database operations.
Deduplicate the standalone `prismarine generate-client` prohibition (stated in Rule 5 and again as a note in workflow step 3) to trim tokens.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and directive — numbered rules, a layout tree, and code with almost no padding or explanation of concepts Claude already knows (no "what is DynamoDB" prose). It falls short of 5 due to minor redundancy: the prohibition on standalone `prismarine generate-client` is stated in Rule 5 and repeated as a parenthetical note in step 3, and the 'Must be ABOVE @c.model' ordering appears in both Rule 4 and the code comment. It is above 3 because the excess is trimming-level, not unnecessary explanation. | 4 / 5 |
Actionability | Mostly executable guidance: complete model definition code, a full resources.yaml block, exact `uv run easysam --environment dev generate .` commands, and copy-paste CRUD examples covering put, conditional put, get, and index query. It misses 5 because the required `DynamoAccess` module (Rule 6 and the layout show `common/dynamo_access.py` exporting `get_dynamo_access()`) is mandated but never exemplified, leaving a gap in the primary workflow. It is above 3 because nothing is pseudocode and the common cases are covered. | 4 / 5 |
Workflow Clarity | The Data Access Workflow is a clearly sequenced 4-step process (define models → configure resources.yaml → generate/deploy → execute CRUD), with some checkpoints present: generate is noted to validate the schema, and the CRUD step shows error handling via `DbConditionFailed`/`DbNotFound`. It does not reach 5 because there is no explicit validate-then-fix-then-retry loop for the deploy step (relevant given database/deploy operations), and stays above 3 because validation and error handling are at least present rather than absent. | 4 / 5 |
Progressive Disclosure | The body is a concise overview (~125 lines) with a clearly labeled Reference Material section pointing to four one-level-deep files (easysam.md, model-definition.md, crud-api.md, cli-usage.md), each annotated with its scope; all four exist in ./references/ and none nest further references. This matches the 5 anchor's clear overview with well-signaled, one-level-deep references and easy navigation; there is no inline content that belongs in a separate file. | 5 / 5 |
Total | 17 / 20 Passed |