Conciseness

Mostly lean: terse tables for commands, templates, channels, and state transitions, with no explanation of git or worktree basics Claude already knows. Minor trim opportunities remain — the 'When This Skill Activates' section duplicates the description's trigger role, and the Installation section adds little. Anchor 4 ('efficient; minor instances of over-explanation') fits better than anchor 5.

Actionability

Mostly executable guidance: slash-command table, concrete script invocations ('python scripts/dag_analyzer.py --frontier --session {id}', result_ranker.py with flags), a copy-paste agent prompt template, and a post format. Minor gaps — LLM-judge mode ('coordinator ranks by quality') is direction without a concrete procedure. Matches anchor 4, not 5.

Workflow Clarity

The INIT → DISPATCH → MONITOR → EVALUATE → MERGE lifecycle is clearly sequenced with commands per phase, a state-transition table, and proactive failure triggers (crashed agents, no improvement, orphan worktrees). Evaluation precedes merge, but there is no verification that the winner is safe to merge (tests green, conflict check) before the destructive merge/archive/cleanup — a minor validation gap matching anchor 4.

Progressive Disclosure

Section structure is well organized and references are clearly signaled, but scored against the actual bundle: every referenced file ('references/agent-templates.md', all five scripts in the Scripts table) is missing — no references/ or scripts/ directories exist — leaving only dangling references. The ~250-line body also inlines material (DAG model, evaluation modes) that belongs in separate files. Broken references place it at anchor 3 rather than 4.

Specificity

Lists multiple concrete actions covering the full lifecycle — 'spawns N parallel subagents competing on the same task via git worktree isolation', 'results are evaluated by metric or LLM judge', 'the best branch is merged' — with comprehensive coverage of spawn, evaluate, and merge. Anchor 5 fits; anchor 4 would require coverage gaps that are not present.

Completeness

Explicitly answers both 'what' (spawn N competing subagents in isolated worktrees, evaluate by metric or LLM judge, merge the best branch) and 'when' ('Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration') with concrete trigger cases. Clearly matches anchor 5; anchor 4's 'when could be more explicit' does not apply.

Trigger Term Quality

Good natural keyword coverage ('multiple approaches tried in parallel', 'code optimization', 'content variation', 'research exploration', 'parallel competition'), but common variations users would actually say ('fan-out', 'tournament', 'have agents compete', 'A/B test') are absent from the description. Matches anchor 4 rather than 5, which requires synonym-level coverage.

Distinctiveness Conflict Risk

The worktree-based parallel-competition niche is distinct with specific triggers, but 'any task that benefits from parallel competition' is a broad catch-all that overlaps general multi-agent orchestration skills. Minor overlap risk matches anchor 4 rather than anchor 5's 'clear niche with minimal conflict risk'.