Content
81%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 well-structured, highly actionable workflow with excellent sequencing and validation feedback loops. The main weakness is that the referenced bundle files (two reference docs and the baseline_stats.py helper script) are missing, which breaks both the progressive-disclosure navigation and the executability of the core baseline step.
Suggestions
Ship the missing bundle files — at minimum scripts/baseline_stats.py (central to step 3), references/threshold-defaults.md, and references/volume-floor-alerts.md — so the referenced navigation and the baseline-threshold pipeline actually work.
If baseline_stats.py cannot be bundled, inline its percentile-to-threshold logic or give a self-contained fallback so the baseline step is executable without an external dependency.
Tighten the few emphasis/framing sentences (e.g. the opening 'measurement problem' paragraph, 'An alert with no destination is silent') to push conciseness toward fully lean.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and information-rich with tight decision tables and specific parameters, assuming Claude's competence throughout; only minor framing/emphasis sentences ('An alert with no destination is silent', the philosophical opener) could be trimmed, keeping it just short of fully lean. | 4 / 5 |
Actionability | Guidance is concrete with exact tool names, parameters, default-value tables, and a copy-paste bash invocation; however the central baseline step depends on scripts/baseline_stats.py, which is referenced but not present in the bundle, leaving an execution gap that prevents a top score. | 4 / 5 |
Workflow Clarity | A clearly sequenced six-step workflow (triage, narrow, baseline, draft & simulate, iterate, ship) with explicit validation via simulate, feedback loops driven by the fire_count and health-flag decision tables, a 3-round iteration cap, and a confirmation checkpoint before wiring to production channels. | 5 / 5 |
Progressive Disclosure | Structure and signaling are strong — lean inline overview with clearly marked one-level-deep references to threshold-defaults.md, volume-floor-alerts.md, and baseline_stats.py — but the referenced bundle files (references/, scripts/) do not exist, so the navigation is broken rather than 'easy', capping the score below 5. | 4 / 5 |
Total | 17 / 20 Passed |