Conciseness

The body is lean and assumes Claude's competence — no space is spent explaining what Hamiltonians or NumPy are, and the prose is limited to decision guidance (When to Use / Do NOT Use, comparison table). The only trimming candidate is matplotlib boilerplate (xlabel/ylabel/grid/legend lines) in the Kepler example, which is cosmetic rather than skill-relevant, matching the 'minor instances of over-explanation' anchor rather than the every-token-earns-its-place anchor 5.

Actionability

All four workflows are complete, executable, copy-paste-ready NumPy code: the leapfrog implementation includes working Kepler initial conditions, a printed energy-conservation check, and Yoshida coefficients spelled out. The examples cover the common cases (2D Kepler, 3-body figure-8, Poincaré section), fully matching the 'copy-paste ready code covering common cases' anchor.

Workflow Clarity

The four core workflows are numbered and self-contained, with an embedded checkpoint (the energy-drift check in workflow 1) and a symptom→fix Troubleshooting table providing error-recovery guidance. Validation checkpoints are not woven into workflows 2–4 and the document presents parallel alternatives rather than one validated sequence, so it matches 'clear sequence with most checkpoints present; minor validation gaps' rather than the full feedback-loop anchor. No cap applies since the operations are non-destructive.

Progressive Disclosure

No bundle files exist (no references/, scripts/, or assets/), so everything is inline in one file. Structure is good — clear section headers, comparison tables, a troubleshooting table — but roughly 150 lines of code with secondary workflows (N-body, Poincaré section) inlined in SKILL.md would fit the disclosure model better as one-level-deep reference files. This matches 'good structure; most content appropriately placed; minor organization gaps' rather than a lean overview with well-signaled references.

Specificity

The description lists multiple concrete capabilities — 'symplectic integrators (leapfrog, Yoshida)', 'Poisson brackets', 'canonical transformations', 'action-angle variables', 'KAM theory analysis' — with comprehensive coverage of the skill's domain. No vague filler; each phrase names a distinct action.

Completeness

Both parts are present: a clear 'what' (the enumerated capability list) and an explicit 'when' ('Use for energy-conserving long-time integration of conservative systems'). The 'when' clause is a single, somewhat technical trigger rather than multiple concrete user-mention phrases, so it sits between the explicit-but-could-be-more-specific anchor 4 and the fully concrete anchor 5.

Trigger Term Quality

Good domain keywords ('Hamiltonian', 'symplectic', 'leapfrog', 'energy-conserving', 'conservative systems'), but common user phrasings the body itself identifies — 'N-body', 'celestial mechanics', 'molecular dynamics', 'energy drift' — are absent. Coverage is solid with a few natural synonyms missing, matching anchor 4 rather than the comprehensive anchor 5.

Distinctiveness Conflict Risk

A clear niche — Hamiltonian/symplectic mechanics with named integrators — that would not plausibly fire for a generic ODE or plotting skill; the body even contrasts itself against standard 'ode-solver' usage. Minimal conflict risk.