Conciseness

The body contains no educational padding (it never explains concepts Claude already knows) and its tables/diagrams are token-efficient, but it is noticeably repetitive and over-inlined: the dispatch boilerplate 'passing the model from `.arness/agent-models/code.md` as the `model` parameter (see ... "Dispatch convention" for fallback)' appears verbatim three times (Steps 2.7, 3d, 3.5b), Step 2.5b re-states the six scope-router scoring steps that already live in scope-router-criteria.md ('The same scope router used by arn-planning (Step 3C) is applied here per feature'), and the ~60-line Complex Phase Upgrade Gate branches in full procedural detail inline. This fits 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than the efficient-but-trimmable anchor 4, and is well above the verbose anchor 2 since nothing is concept-explanation filler.

Actionability

Fully executable guidance throughout: exact commands ('gh issue list --state open --limit 20 --json number,title,labels', 'git checkout -b plans/<date>-batch'), exact AskUserQuestion prompts with complete option sets, concrete naming conventions ('SWIFT_<kebab-case-name>', 'PLAN_PREVIEW_<spec-name>.md'), explicit output paths, and precise retry policies ('Retry that specific feature's batch-analyzer (up to 2 retries) ... after 3 total attempts'). Placeholders like [N] and [Feature Name] are clearly parameterized template slots, not vague directions — this matches the copy-paste-ready anchor.

Workflow Clarity

The multi-step process is clearly sequenced (Steps 0, 1, 1a-1c, 2, 2.5-2.7, 3a-3e, 3.5a-3.5c, 4-6) with explicit validation checkpoints and feedback loops for this batch operation: pre-analysis failure retries with user choice ('Never silently fall back to a degraded flow'), spec-phase error handling with Retry/Skip/Abort, planner failure retry-then-ask, tracker status revert-on-failure ('revert the feature's status from `in-progress` back to `pending`'), plan approval gates before save-plan, and post-pull verification that plans exist on disk. This satisfies the batch-operation feedback-loop requirement and matches the anchor for explicit validation steps with error-recovery loops.

Progressive Disclosure

Structure is good: the two local references are real files (references/backlog-selection.md, references/plan-shipping.md), clearly signaled at point of use ('Read ... and follow its procedure'), one level deep, and cross-skill references are consistently path-qualified under ${CLAUDE_PLUGIN_ROOT}. However, the ~600-line body inlines content that belongs in a reference — most notably the ~60-line Complex Phase Upgrade Gate (3.5c) with its session-memory model and two-tier preference lookup (which even points to preferences-schema.md), and the re-stated scope-router scoring steps of 2.5b — which is why this is 'good structure with minor organization gaps' rather than the cleanly split anchor 5.

Specificity

Quotes several concrete actions — 'Pre-analyzes all selected features in parallel, then guides sequential spec review with pipelined plan generation' — plus chaining behavior ('chains to arn-code-batch-implement upon completion'). It is not a 5 because the description covers only the headline pipeline actions and omits other capabilities the skill performs (scope assessment/tier routing, plan shipping, source detection from GitHub/Jira), which are only weakly implied via 'from the greenfield Feature Tracker, GitHub issues, or Jira issues'. It is above a 3 because it lists multiple specific parallel/sequential/pipelined actions rather than just 1-2.

Completeness

Both questions are explicitly answered: 'what' via 'Pre-analyzes all selected features in parallel, then guides sequential spec review with pipelined plan generation' and 'when' via 'This skill should be used when the user says [18 trigger phrases] ... or wants to plan multiple features from the greenfield Feature Tracker, GitHub issues, or Jira issues in a single session.' It even adds a negative trigger ('For single-feature planning, arn-planning is the correct entry point'), exceeding the anchor-5 example rather than falling between anchors.

Trigger Term Quality

Comprehensive natural trigger coverage: 'batch planning', 'batch plan', 'plan multiple features', 'plan all features', 'plan unblocked features', 'plan the backlog', 'plan from backlog', 'batch spec and plan', 'plan the next batch', 'plan these features', 'batch plan GitHub issues', 'batch plan from Jira', 'multi-feature plan', 'sequential planning', plus the skill's own name 'arn-code-batch-planning' and a plain-language condition ('wants to plan multiple features ... in a single session'). This matches the anchor for comprehensive coverage of natural terms including synonyms and variations; nothing common is missing.

Distinctiveness Conflict Risk

It carves out a clear niche — batch/multi-feature planning — with batch-specific triggers ('batch plan', 'plan the next batch', 'multi-feature plan') and explicitly disambiguates the closest sibling: 'For single-feature planning, arn-planning is the correct entry point.' It also states entry/exit relationships ('invoked directly or after arn-brainstorming completes and chains to arn-code-batch-implement'), which minimizes wrong-skill triggering. The trigger terms are all multi-feature phrasings, so overlap with single-feature planning skills is minimal.