Conciseness

The body is mostly instructional, but the '[Extended thinking: ...]' paragraph (~90 words of pure workflow narration a competent model already infers), the stray 'Performance optimization target: $ARGUMENTS' line, and an Example section containing only a user request with no output are unnecessary padding. Not score 2 because the bulk is actionable instruction rather than concept explanation.

Actionability

Concrete guidance throughout: named subagent types, full copy-paste prompts, specific tooling (k6/Gatling/Artillery, OpenTelemetry, DataDog/Grafana/PagerDuty), and quantified success criteria (P95 < 200ms, LCP < 2.5s). Held below 5 because '{context_from_phase_1}' placeholders are never concretely wired and some prompts stay at the recommendation level.

Workflow Clarity

Five clearly sequenced phases with each step's context explicitly sourced from prior steps, plus validation via Phase 4 load testing, regression budgets, automatic rollback triggers, and a Safety section covering production load tests and gradual rollouts. Below 5 because there are no explicit if-validation-fails-then-retry feedback loops at step level.

Progressive Disclosure

Section and phase structure is good, but no bundle files exist and all 13 full subagent prompt templates are inlined in a single ~150-line file — content that clearly belongs in separate reference files. This matches 'some structure... content that should be separate is inline' rather than the well-split anchor 4-5 patterns.

Specificity

The description names the domain (application performance) and several action areas ('profiling, observability, and backend/frontend tuning'), but these are generic category labels rather than concrete verb-on-object actions like 'extract text' or 'fill forms'. It goes beyond 1-2 actions but lacks the specificity of the anchor-4 example.

Completeness

Both 'what' (optimize end-to-end application performance with profiling, observability, and tuning) and 'when' ('Use when coordinating performance optimization across the stack') are explicitly present, but the when-clause circularly restates the what instead of offering concrete trigger phrases, matching anchor 4 rather than 5.

Trigger Term Quality

Good coverage of natural terms users would say ('performance', 'profiling', 'optimization', 'backend', 'frontend'), though common phrasings like 'slow', 'latency', 'speed up', or 'load testing' are missing, and 'coordinating performance optimization across the stack' is meta-language users would not naturally say.

Distinctiveness Conflict Risk

'End-to-end application performance' is a broad domain that overlaps with narrower skills (database optimization, frontend performance, load testing); the 'coordinating across the stack' framing narrows it somewhat but does not establish a clearly distinct niche with unique triggers.