Conciseness

The body is lean and assumes Claude's competence: every section is a bare command block or output example ('python {skill_path}/scripts/log_results.py --dashboard', 'cat .autoresearch/{domain}/{name}/loop.json 2>/dev/null') with no concept explanations or padding. It clearly matches the anchor 'Lean and efficient; every token earns its place' and not the level below, which requires minor over-explanation that is absent here.

Actionability

Guidance is mostly executable and concrete: per-mode commands like 'python {skill_path}/scripts/log_results.py --experiment {domain}/{name}' and export invocations '--format csv --output results.csv', plus a concrete loop-status format template. It falls short of fully copy-paste ready because '{skill_path}', '{domain}', '{name}' placeholders must be substituted and the referenced 'scripts/log_results.py' is not present in the provided bundle, so the commands cannot be verified as executable — matching 'mostly executable guidance; concrete code or commands with minor gaps' rather than the fully executable anchor.

Workflow Clarity

Each invocation mode (single experiment, domain, full dashboard, export) has a clear command sequence, and the single-experiment flow includes a conditional checkpoint ('If loop.json exists, show: Active loop: every {interval} (cron ID: {id}, started: {date})') and the instruction 'For each experiment, also check for loop.json and show loop status'. It is below the level-5 anchor because there are no explicit validation or recovery steps for failure cases (e.g., unknown experiment name or script error), though as a read-only reporting skill the risk is low.

Progressive Disclosure

The body is a compact, well-sectioned overview (Usage, What It Does, Output Example) that delegates logic one level deep to 'scripts/log_results.py' rather than inlining implementation. It does not reach 5 because no 'scripts/' directory exists in the bundle to verify that referenced path, and the '{skill_path}' placeholder convention is used without explanation — minor organization gaps per the level-4 anchor.

Specificity

'Show experiment dashboard with results, active loops, and progress' names the domain (experiment dashboard) and enumerates concrete content items, but coverage is incomplete: the skill also supports single-experiment detail, domain filtering, and CSV/markdown export, none of which are mentioned. This matches 'Names domain and 1-2 concrete actions, but not comprehensive' rather than level 4, which requires several listed actions with only minor gaps.

Completeness

It explicitly answers both questions: what ('Show experiment dashboard with results, active loops, and progress') and when ('Use when the user runs /ar:ar-status or asks how an autoresearch experiment is going') with concrete trigger phrases. This directly matches the level-5 anchor; the level-4 anchor applies only when the 'when' clause is less explicit.

Trigger Term Quality

Good keyword coverage with natural triggers: the exact command '/ar:ar-status' and the natural user phrase 'asks how an autoresearch experiment is going', plus terms like dashboard, results, loops, and progress. It falls below the comprehensive level-5 anchor because common variations such as 'experiment status', 'check on my experiment', or 'experiment report' are missing.

Distinctiveness Conflict Risk

The description is scoped to a clear niche — autoresearch experiments — and anchored by the distinct exact-command trigger '/ar:ar-status', giving minimal conflict risk with generic status or reporting skills. It matches 'Clear niche with distinct triggers; minimal conflict risk'.