Content
73%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 strong, disciplined browser-automation skill: sequencing, validation checkpoints, and error-recovery feedback loops are excellent, and the reference/script bundle is real and well-linked. Its main weakness is token efficiency — several sections repeat the same facts (Studio inventory, default-prompt warning, async rules) that belong in a single place.
Suggestions
State the Studio output inventory once (in Action 3) and have Q1/Q3 reference it, cutting two of the three repeated lists and hedging ('the UI evolves fast') duplication.
Keep one inline custom-prompt exemplar and defer the rest to references/studio_output_custom_prompts.md, which already contains per-output-type templates; likewise reduce the inline async table since scripts/async_action_classifier.py and references/async_action_discipline.md already encode the verdicts.
Trim or compress the repeated 'Why I'm asking' rationale blocks and the four-fold 'default prompts are mediocre' admonition to a single statement plus the anti-patterns entry.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly functional but noticeably redundant: the Studio inventory list appears three times (Q1, Q3, Action 3), the 'default Studio prompts produce mediocre output' admonition appears four times, and async wait/notify rules are restated across the Action 3 workflow, the Critical Async Behavior section, the classifier script's table, and its reference file; screenshot-first/find-before-click sections also overlap browser_automation_canon.md. Not a 2 because nothing is generic filler — every repetition is at least substantive. | 3 / 5 |
Actionability | Gives concrete, executable guidance for the common cases: per-source-type UI click paths, exact wait durations (3–5s chat, 5–30s ingestion, <30s auto-summary), a full error-recovery table, and copy-paste script invocations ('python3 scripts/async_action_classifier.py --action "video overview"'). Falls short of 5 because some UI steps remain abstract ('Locate chat input (semantic find or screenshot coordinates)') with no worked example of a semantic find call. | 4 / 5 |
Workflow Clarity | Multi-step processes are clearly sequenced (Step 0 context check → Q1–Q4 intake → notebook discovery → per-action flows) with explicit validation checkpoints (screenshot before every meaningful interaction, confirm ingestion spinner, verify generation started before fire-and-notify) and genuine feedback loops in the error table ('retry once', 'ask user if they want to retry', 'look for Discover more before declaring it unavailable'). | 5 / 5 |
Progressive Disclosure | Good structure with well-signaled, one-level-deep references (browser_automation_canon.md, studio_output_custom_prompts.md, async_action_discipline.md) that all resolve to real files, plus a Tooling table for the three scripts. Falls short of 5 because the four inline custom-prompt examples and the inline async/wait table duplicate content that the referenced canon files already carry, instead of deferring to them. | 4 / 5 |
Total | 16 / 20 Passed |