Content
88%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-engineered orchestration body: lean, highly actionable routing with exact commands, paths, and question wording, and a workflow with explicit validation and feedback loops. The main improvements are trimming the Step 2 enumeration that duplicates data-discovery.md and reducing second-level indirection through ../shared/ pattern files not shipped in the bundle.
Suggestions
Conciseness: drop the inline enumeration of discovery checks in Step 2 (tables/columns, fan-out, cardinality, payload, etc.) and trust references/data-discovery.md, keeping only 'run it without asking' plus the ask-only-what-data-can't-answer rule.
Progressive disclosure: inline or summarize the essential contract from <skill_dir>/../shared/*.md pattern steps (project_state.md bootstrap, agent build, registration) into references/*.md so no instruction path requires reading a file outside the skill bundle.
Progressive disclosure: consider listing project_templates/ and tools/dash_to_html.py in the Quick reference with one-line purposes, since they are invoked by name but never described in the overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and directive with no explanations of concepts Claude already knows (no 'what a dashboard is', no library tutorials) — every section is instruction. It falls at anchor 4 rather than 5 because of minor trimmable redundancy, e.g. Step 2's enumeration ("tables and columns, the business time column and timezone, each metric validated as a formula on live data, joins checked for fan-out, the data-quality gate, dimension cardinality, payload estimate, query times") restates the contents of references/data-discovery.md, and the Treasure AI Studio paragraph is tangential to the core flow. | 4 / 5 |
Actionability | Concrete, executable guidance throughout: exact CLI ("offer the likely ones from `tdx databases`"), exact paths ("agent_outputs/<project_slug>/project_state.md", ".claude/skills/<project_slug>-dashboard/"), copy-ready AskUserQuestion option labels ("'Build, run and validate (Recommended)' / 'Change names first' / 'Skip the workflow — build directly'"), and specific thresholds ("spot-check ≥ 3 KPIs against the source (exact match)", "data < 500 KB ideal, ≤ 2 MB hard stop"). Per the scoring note, an instruction-only skill without inline code is not penalized when the guidance is this actionable; it does not sit at anchor 4 because no common case lacks the specific steps to execute. | 5 / 5 |
Workflow Clarity | A clearly sequenced 4-step flow with an overview table, explicit validation checkpoints, and a feedback loop: "If validation fails, fix and re-run before Step 4", "validate the SINK tables against the source", "spot-check ≥ 3 KPIs against the source (exact match)", and "run its build check". The batch/database validation requirement is fully met, and project_state.md's Current phase / Next Action mechanism provides resumable checkpoints — matching anchor 5's 'explicit validation steps; feedback loops for error recovery'. | 5 / 5 |
Progressive Disclosure | Good structure: a ~75-line overview where each step names exactly one reference to read ("Read `references/intake.md`", "Read `references/data-discovery.md`", "Read `references/workflow-setup.md`", etc.), all 8 referenced files exist in the bundle and are one level deep and clearly signaled. It stays at anchor 4 rather than 5 because the body additionally points to `project_templates/`, `tools/dash_to_html.py`, and `<skill_dir>/../shared/*.md` files that are not present in the provided bundle, and several references chain onward to `../shared/` pattern documents (e.g. agent-setup.md → customer_agent_pattern.md), adding a second level of indirection. | 4 / 5 |
Total | 18 / 20 Passed |