Conciseness

Mostly efficient — concrete commands, a structured workflow, and a domain-specific template — but with several tightenings available: the 'English' requirement appears twice ('All analysis thinking should be conducted in English', 'Output Markdown files must be in English', plus a third mention in the frontmatter), the chart-images-are-optional point is repeated four times, and Step 5's 'Required Sections' list duplicates the output template that follows it. This matches anchor 3 ('mostly efficient but includes some unnecessary explanation or could be tightened') rather than anchor 2, since there is no padding that explains concepts Claude already knows.

Actionability

Concrete, executable commands are provided ('python3 scripts/analyze_sector_rotation.py --json', '--save --output-dir reports/'), along with a specific probability scale, a full output template, and named data files with their purposes. It falls short of anchor 5 only because the chart-image analysis path and the script's expected output format are described abstractly rather than shown with an example, leaving a minor gap.

Workflow Clarity

The five-step workflow is clearly sequenced with concrete sub-steps, and there is a data-quality checkpoint ('If a data freshness warning appears, note it in the analysis') plus guidance to flag contradictory signals and reassess confidence. It matches anchor 4 ('clear sequence with most checkpoints present; minor validation gaps') — anchor 5 would require an explicit error-recovery loop such as what to do if the CSV fetch fails, and since this is a read-only analysis skill the destructive/batch cap does not apply.

Progressive Disclosure

The body is a well-organized overview pointing one level deep to real, existing files: 'references/sector_rotation.md' (signaled both in Step 2 and in Resources), the analysis script, and three sample chart assets — all verified present on disk. It sits at anchor 4 rather than 5 because some content that could live in the knowledge base (the ~15-line Probability Guidelines section, which overlaps the referenced 'Probability Assessment Framework' in sector_rotation.md, and the full output template) is inlined in SKILL.md, leaving minor organization gaps.

Specificity

The description names the domain ('sector rotation patterns and market cycle positioning') and a couple of concrete actions ('fetches sector uptrend data from CSV', 'optionally accepts chart images'), but the richer capabilities (ranking sectors, risk regime scoring, overbought/oversold flags) appear only in the body, not here. It matches anchor 3 — domain plus 1-2 concrete actions — and falls short of anchor 4's 'several specific actions' since the analysis outputs themselves are not enumerated.

Completeness

Both questions are answered explicitly: what it does ('fetches sector uptrend data from CSV', 'analyzing sector rotation patterns and market cycle positioning') and when to use it ('Use this skill when the user requests sector rotation analysis, cyclical vs defensive assessment, overbought/oversold identification, or market cycle phase estimation'). This matches anchor 5's clear what + when with concrete trigger phrases; the 'when' is not merely implied as in anchor 4.

Trigger Term Quality

Natural phrases a user would say are present: 'sector rotation analysis', 'cyclical vs defensive assessment', 'overbought/oversold', 'market cycle phase estimation'. Coverage is good but misses common variations such as 'sector performance' or 'which sectors are leading', so it sits at anchor 4 rather than anchor 5's comprehensive synonym coverage.

Distinctiveness Conflict Risk

'Sector rotation' and 'market cycle positioning' form a clear niche with distinct, specific triggers, but the description could overlap with generic market-analysis or technical-analysis skills (it mentions 'market cycle phase estimation' broadly). Anchor 4 ('mostly distinct; minor overlap risk with closely related skills') is the best fit — anchor 5 would require zero meaningful overlap with adjacent finance skills.