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.
The content is a well-structured, highly actionable sequencer with explicit gates, resumability, and feedback loops, and it appropriately offloads detail to two one-level-deep references; its main weakness is token padding from repeated progress-display blocks.
Suggestions
Replace the per-step ASCII progress-display blocks with a single defined format referenced once, or show only the active-stage variant, to cut repeated padding across the ~13 steps.
Consider condensing the repeated gate-option tables into a compact shared format now that the full gate table already appears in the 'Decision Gates' section.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and mostly earns its tokens (gates table, state-detection table, exact tool invocations), but repeats a near-identical ASCII progress-display block for each of the ~13 steps and verbose gate-option tables that a leaner version could collapse, fitting anchor 2. | 2 / 3 |
Actionability | It provides fully concrete, executable guidance: exact Skill invocations ("Skill: arn-code:arn-code-feature-spec"), exact agent names, exact file paths, exact AskUserQuestion option text, and exact artifact-detection rules, matching the copy-paste-ready anchor 3. | 3 / 3 |
Workflow Clarity | The 13-step pipeline is clearly sequenced with 7 explicit gates (G1–G7), a resumability/state-detection table, a conflict-detection loop (G5), and a re-test feedback loop (G6), giving clear checkpoints and feedback loops for the risky batch pipeline. | 3 / 3 |
Progressive Disclosure | SKILL.md is an overview/sequencer that defers detail to two real, one-level-deep reference files (assessment-protocol.md, orchestration-flow.md) signaled with exact Read paths, while keeping only the sequencing logic inline, matching the clear-overview anchor 3. | 3 / 3 |
Total | 11 / 12 Passed |