Conciseness

The body is dense with non-generic domain knowledge (fill-vs-round-trip pairing, cost arithmetic at 7 bps, the engine's signed drawdown) and avoids explaining concepts Claude already knows. However, the Purpose and When-to-Use sections partly restate the frontmatter description, and a few rationale sentences (e.g., "so you see a spec mistake in a second instead of after a long load") could be trimmed — matching the score-4 anchor of efficient with minor instances that could be tightened, not the fully lean score-5 anchor.

Actionability

Guidance is copy-paste ready: a complete executable spec JSON with all fields, the exact `python3 scripts/run_backtest.py --spec strategy.json --data bars.csv --symbol BTCUSDT --json-out result.json` command, and a paste-ready evaluate_backtest.py invocation with real flag values. This matches the fully-executable top anchor with specific examples covering the common case.

Workflow Clarity

The four-step workflow has explicit validation checkpoints and feedback loops: the script "validates the spec before it touches the data", step 3 directs reading warnings before numbers with named warning conditions and three stop conditions, and instructs "fix the setup and run again" on any warning. This matches the top anchor of clear sequence with explicit validation and error-recovery loops.

Progressive Disclosure

SKILL.md is a genuine overview: field-level detail lives in references/strategy_spec.md and conversion detail in references/metric_bridge.md (both verified to exist, one level deep, each with a one-line description of its scope), and the four scripts are listed with their roles. This matches the top anchor of a clear overview with well-signaled one-level-deep references and easy navigation.

Specificity

The description lists three concrete pipeline actions — "Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs" — which comprehensively covers what the skill does. This matches the anchor for multiple specific concrete actions with comprehensive coverage, not the score-4 anchor with minor gaps.

Completeness

It explicitly answers both questions: the what ("Runs a declarative strategy spec over OHLCV bars... pairs the fill log into round trips... emits the eight inputs") and the when ("Use when the user wants to execute a backtest, measure a rule they have described, obtain win rate / average win / average loss / max drawdown from real bars, or feed backtest-expert with measured numbers"). Concrete trigger phrases are present, matching the top anchor.

Trigger Term Quality

Strong natural phrases users would say: "execute a backtest", "measure a rule they have described", "win rate / average win / average loss / max drawdown from real bars", "measured numbers instead of estimates". A few common variations are still missing (e.g., "test a trading strategy", "historical data/bars", "strategy performance"), which fits the score-4 anchor of good coverage with a few natural terms missing rather than comprehensive synonym coverage.

Distinctiveness Conflict Risk

The description occupies a clear niche — running a named engine (manifoldbt) over OHLCV bars and feeding the companion backtest-expert skill — with triggers like "execute a backtest" and "feed backtest-expert with measured numbers instead of estimates" that would not fire for unrelated skills. Minimal conflict risk, matching the score-5 anchor.