Conciseness

The body is command-first and assumes competence — no space is spent explaining what evals or models are, and warnings are one sentence each ("running evals from there won't work and changes would be overwritten"). It is not a 5 because the Run labels section spends ~20 lines on label-composition ingredients and six example labels that could be compressed to two lines.

Actionability

Every phase gives copy-paste-ready bash commands with concrete flags (`tessl eval run <path> --agent=claude:<model> --label <run-label>`, `tessl eval view <id> --json`, `tessl eval retry <id>`), plus exact output formats to parse (`Eval run started: <id>`, `Status: ✔ Completed`) and rendered table templates for the reports. The common cases are fully covered.

Workflow Clarity

Phases 1–7 are clearly sequenced with explicit checkpoints: verify scenarios and login before running (1.2, 1.3), poll each run to Completed/Failed before starting the next model (Phase 4), retry on failure (`tessl eval retry <id>`), and a "When to stop" section. This is a batch, cost-incurring operation and the feedback loop (poll → fail → retry → re-check) plus the explicit warning against concurrent runs satisfies the validation requirement.

Progressive Disclosure

The body is well-organized into clearly headed phases with a navigable overview, and it appropriately points to sibling skills (setup-skill-performance, optimize-skill-performance) rather than duplicating them. It is not a 5 because there is no bundle at all and ~220 lines of inline reference-style material (six label examples, four failure-pattern definitions, table templates) could live in a one-level-deep reference file.

Specificity

The description lists several concrete actions — "Run task evals across multiple Claude models", "compare results side-by-side", "identify model-specific gaps versus universal plugin gaps", "validate a skill before publishing" — giving comprehensive coverage of the workflow. It falls short of a 5 only because "and optimise" is a vague action with no concrete counterpart (the body delegates that to a separate optimize-skill-performance skill).

Completeness

It explicitly answers both questions: the "what" is stated upfront ("Run task evals across multiple Claude models, compare results side-by-side, and optimise") and the "when" is a full "Use when you want to…" clause with six concrete trigger scenarios. Matches the level-5 anchor's structure exactly; not level 4 because the when-clause is already explicit and specific, not merely improvable.

Trigger Term Quality

Trigger phrases are natural user language and include synonyms and specifics: "benchmark a skill across models", "compare haiku vs sonnet vs opus performance", "run multi-model comparison or benchmark reports", "works for all model tiers", "validate a skill before publishing it to the registry". Naming the actual model tiers users would say (haiku/sonnet/opus) gives comprehensive coverage; nothing obvious is missing.

Distinctiveness Conflict Risk

The multi-model comparison niche is clear and triggers like "compare haiku vs sonnet vs opus performance" are unlikely to fire the wrong skill. Minor overlap risk remains with sibling skills (setup-skill-performance, optimize-skill-performance) since "optimise" and "evaluate" appear in this description's what-clause, keeping it just below the level-5 'minimal conflict risk' anchor.