Content
86%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.
The body is a tight, well-structured foundation document: an executable Python example, concrete cross-language rules, a JSON type-mapping table, and pointed pitfalls including exact failure modes. Its only weaknesses are mild redundancy around the queue-routing rule and the absence of an explicit verification checkpoint for the ID-matching requirement that the skill itself flags as the primary failure source.
Suggestions
State the queue_to_coordinator requirement once instead of three times (inline comment, section prose, and rules list) — collapsing the duplicates would tighten conciseness without losing information.
Merge the 'Both sides need the upstream reference' pitfall with the earlier 'arg only declares the dependency' explanation, since they restate the same rule.
Add a short validation hint for the skill's most fragile operation, e.g. how to confirm the stub queue name exists in queue_to_coordinator or that DAG/task IDs match before running, turning the 'no DAGs' error note into a pre-flight check.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense with non-obvious specifics (stub AST rules, retry_policy ValueError rationale, XCom JSON table) and wastes no tokens explaining what Airflow or XCom generically are. Minor trimmable redundancy keeps it below the top anchor: the queue/queue_to_coordinator rule is stated three times (inline comment, section prose, and the rules list), and "Both sides need the upstream reference" in the pitfalls repeats the earlier "arg only declares the dependency" explanation. | 4 / 5 |
Actionability | The Python DAG example is complete and copy-paste ready (imports, @dag, @task.stub with queue/retries/retry_delay, dependency wiring, invocation), and the rules are concrete and verifiable: "The stub function name is the task ID", "retry_policy is rejected on stubs (@task.stub raises ValueError)", "only pass, ..., or a docstring is allowed in the body". The absence of native-side code is explicit, justified delegation to per-language skills rather than a gap, so the common case is fully covered. | 5 / 5 |
Workflow Clarity | The authoring workflow is clearly sequenced (declare stubs in the DAG with matching IDs, set queue/retries on the stub, delegate native implementation) and the pitfalls section provides error feedback ("Mismatches surface as 'no DAGs' or missing-XCom errors"), which covers the error-recovery side of the top anchor. However, there is no explicit verification step (e.g., a command or check to confirm IDs match or the queue is registered) for the skill's most fragile operation, so it fits 'clear sequence with most checkpoints present; minor validation gaps' better than a 5. | 4 / 5 |
Progressive Disclosure | No bundle files exist (references/, scripts/, assets/ are all absent) and none are needed: the ~125-line body is a compact conceptual foundation whose per-language details are deliberately and clearly delegated to named sibling skills ("authoring-java-sdk-tasks", "configuring-airflow-language-sdks") rather than buried. Sections are well-organized and each is appropriately sized to be inline, matching the well-organized self-contained-skill case. | 5 / 5 |
Total | 18 / 20 Passed |