Content
85%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, highly actionable workflow with clear validation checkpoints and appropriate use of bundle scripts. The only weakness is some over-explanation of environment and implementation internals that an intelligent model does not need.
Suggestions
Trim the interpreter/virtualenv aside in 'Required Scripts' (lines 53-55) to a single sentence; the exact interpreter choice can be inferred at runtime.
Compress the log-relevance rules block (lines 91-104) into a short bullet list; the detailed redaction mechanics belong in the collect script, not the skill body.
Shorten the submit-script implementation detail paragraph (lines 247-253) to what the model must do (relay results, never echo a token) rather than how the script imports settings internally.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean and directive, but passages over-explain environment/interpreter details ('User installations typically run MoviePilot directly in that environment rather than inside a repository-local virtualenv...') and implementation internals, matching the 'mostly efficient but could be tightened' anchor. | 2 / 3 |
Actionability | Provides copy-paste executable script invocations with real flags, two complete draft-JSON templates with all required fields, allowed-value tables, and exact per-reason-code handling, matching the 'fully executable code/commands; copy-paste ready' anchor. | 3 / 3 |
Workflow Clarity | Six clearly sequenced steps with explicit validation checkpoints (gate on no_explicit_feedback_intent, rejection handling, explicit '确认'/'confirm' before submit) and a keyword-mismatch feedback loop, matching the 'clear sequence with explicit validation steps; feedback loops for error recovery' anchor. | 3 / 3 |
Progressive Disclosure | References real, present bundle scripts (collect/prepare/submit_feedback_issue.py plus shared feedback_issue_common.py) via one-level-deep pointers, keeping heavy detail in the scripts while the body stays an overview, matching the 'clear overview with well-signaled one-level-deep references' anchor. | 3 / 3 |
Total | 11 / 12 Passed |