Content
86%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, well-structured skill body: executable DQL for every workflow, concrete troubleshooting, and exemplary progressive disclosure with verified one-level-deep references. The main improvement opportunity is tightening repetition (the three near-identical OneAgent queries) and slimming the Cloud-Specific Attributes section that duplicates the reference file.
Suggestions
Collapse the three OneAgent traverse queries into one example with a note that the fieldsAdd line varies by field (mode vs version vs both), trimming ~20 lines.
Replace the inlined AWS/Azure/GCP/Kubernetes attribute lists with a short summary and a pointer to references/inventory-discovery.md#multi-cloud-hosts, since the reference already covers this in more depth.
Fix the line 86 link: the text reads 'see references/inventory-discovery.md' but the href is the local anchor #cloud-specific-attributes.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and information-bearing — every workflow pairs a one-line purpose with an executable DQL query, and the troubleshooting table is pure signal (e.g. "Use `dt.agent.monitoring_mode`; `dt.agent.monitoring.mode` (dot) always returns null"). Not a 5: the OneAgent section repeats the same traverse query three times varying only the fieldsAdd line, and the Cloud-Specific Attributes section duplicates material that references/inventory-discovery.md already covers. Not a 3: there is no padding explaining concepts Claude already knows; prose sections (Response Construction, Analytical Workflows) carry genuinely non-obvious domain guidance such as the horizon-vs-lookback distinction and novelty-type exclusion rule. | 4 / 5 |
Actionability | Quotes: nine complete copy-paste-ready DQL workflows (e.g. "timeseries { cpu = avg(dt.host.cpu.usage), ... } | filter arrayAvg(cpu) > 80"), four reusable dql-template patterns, and concrete pitfalls with exact field names ("GCP project uses two dots: `gcp.project.id` not underscore"). Guidance is fully executable and covers the common cases, matching the 5 anchor. | 5 / 5 |
Workflow Clarity | Workflows are numbered and titled (1-9), each with a clear purpose line, and the analytical workflows give explicit numbered sequences ("1. Construct the timeseries query ... 2. Pass it to the appropriate analysis tool") plus decision rules for choosing between detectors. Not a 5: validation checkpoints are implicit — e.g. time-range and OneAgent-deployment verification live only in the troubleshooting table rather than as in-line checks — though these are read-only queries so no destructive-operation cap applies. Well above a 3, where sequences would be present but checkpoints and decision guidance largely absent. | 4 / 5 |
Progressive Disclosure | Quotes: "This skill uses **progressive disclosure**. Start here for 80% of use cases" plus a dedicated "When to Load References" section giving per-file load conditions, and anchor-linked pointers throughout (e.g. "see [references/host-metrics.md](references/host-metrics.md#cpu-monitoring)"). All four referenced files exist and their headings match the cited anchors; references are exactly one level deep. This matches the 5 anchor — the single blemish (line 86 links text 'references/inventory-discovery.md' to a local anchor instead of the file) is cosmetic and the target content is available either way. | 5 / 5 |
Total | 18 / 20 Passed |