Content
70%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is highly actionable with executable commands and a real script, and is well-organized into a single one-level-deep bundle. It loses points on conciseness (bulky inline output templates) and workflow clarity (no validation/error-recovery checkpoints for the cost-incurring API pipeline).
Suggestions
Move the full JSON output schema and markdown summary template into a reference file and link to it, keeping only a short example inline.
Add explicit validation/checkpoint steps between phases (e.g. verify an actor succeeded and returned data before proceeding, retry/fallback on actor failure).
Note that the bundle script relies on a Gooseworks proxy (GOOSEWORKS_API_BASE/KEY) not mentioned in the body, which affects actionability of the documented Apify-only flow.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and concrete, but the large inline JSON output example and full markdown summary template (~50 lines each) pad the body with detail that could live in a reference file. | 2 / 3 |
Actionability | Provides copy-paste-ready CLI commands, specific Apify actor inputs as JSON, and a real executable script in the bundle (scripts/analyze_domain.py). | 3 / 3 |
Workflow Clarity | Six phases are clearly sequenced, but this is a cost-incurring batch of external API runs with no explicit validation checkpoints or error-recovery feedback loops, capping workflow clarity at 2. | 2 / 3 |
Progressive Disclosure | Single well-organized script bundle with clear sections (Quick Start, Inputs, Cost, Process phases, Output, Fallback); the referenced scripts/analyze_domain.py is a real file, and references are one level deep. | 3 / 3 |
Total | 10 / 12 Passed |