Content
68%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 efficient, actionable, and well-structured with concrete commands and a clear sequenced workflow, but it lacks an explicit validation/verification checkpoint for batch scraping runs, capping workflow clarity. Adding a verify-results step would lift the score.
Suggestions
Insert a verification checkpoint after Step 4 (e.g., 'Verify the run succeeded and results are non-empty before summarizing') to satisfy the batch-operation validation requirement.
Make the run_actor.js reference a clearly signaled, one-level-deep link rather than an inline path placeholder, so the script dependency is explicit.
Tighten the 'When to Use' bullets and the prerequisites note to remove minor redundancy.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean: tables, copy-paste bash blocks, a checklist, and a terse error-handling list, with no padding explaining concepts Claude already knows; only minor phrasing could be trimmed further. | 4 / 5 |
Actionability | Provides concrete, mostly copy-paste-ready commands for schema fetching and three output-mode script invocations with explicit flags; the unavoidable JSON_INPUT/ACTOR_ID placeholders are the only gaps keeping it from fully executable. | 4 / 5 |
Workflow Clarity | A clear five-step sequenced workflow with a tracking checklist is present, but running Apify scrapers is a batch data-extraction operation with no explicit validation/verification checkpoint in the sequence, which caps workflow clarity at 3 per the rubric. | 3 / 5 |
Progressive Disclosure | Well-organized into clear sections (When to Use, Workflow steps, Error Handling, Limitations) with a single appropriately-signaled script reference; no bundle files are present to verify, but structure is sound with only minor organization gaps. | 4 / 5 |
Total | 15 / 20 Passed |