Conciseness

The body is lean overall: a decision table for Actor selection, tight command blocks, a compact error table, and no explanations of concepts Claude already knows. Not 5 because the "Run Boundaries" section crams roughly nine distinct rules into a single dense paragraph and partially repeats Prerequisites (token privacy), which could be trimmed or split. Not 3 because there is no padding or unnecessary over-explanation.

Actionability

Commands are concrete in shape — `node --env-file=.env "<resolved-skill-directory>/reference/scripts/run_actor.js" --actor "ACTOR_ID" --input 'JSON_INPUT'` with explicit `--output`/`--format` flags and a real error-handling table — but every invocation depends on `run_actor.js`, which does not exist in the bundle (no references/, scripts/, or assets/ directory is present), and the placeholders "ACTOR_ID"/"JSON_INPUT" cannot be filled without it. Not 4 because the central executable artifact is missing; not 2 because the command structure, flags, output formats, and Actor IDs are specific and near-executable.

Workflow Clarity

The sequence is explicit (copyable progress checklist, Steps 1–5) with meaningful pre-launch checkpoints — "Verify prerequisites before any paid run", fetch the Actor schema before calling, "confirm the selected Actor, authorized public-data scope, current input schema, result limits and pricing with the user's request" — plus error-recovery guidance ("Inspect the printed run ID in Console before retrying to avoid duplicate charges"). Not 5 because there is no post-run validation step (Step 5 only reports results without verifying output integrity); not 3 because pre-run validation and error-recovery loops are present for this paid batch operation.

Progressive Disclosure

Sections are well organized (When to Use, Prerequisites, Workflow, Error Handling, Run Boundaries, Limitations) and the only external reference is a single one-level-deep script path embedded in the commands, with no nested references. Not 5 because that sole referenced path (`reference/scripts/run_actor.js`) does not exist in the bundle — no such file or directory is shipped — and the 18-row Actor table is arguably reference material inlined in SKILL.md; not 3 because the structure is clean and easy to navigate for a single-file skill.

Specificity

"Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok" names four concrete analysis dimensions and the four platforms, but relies on the single generic verb "Understand" and never states the actual actions (extracting follower/engagement data via Apify Actors). This matches anchor 3 (domain plus some concrete items, not comprehensive); it is not anchor 4 because it does not list several specific actions, and not anchor 2 because the enumerated analysis targets go beyond a minimal generic statement.

Completeness

The "what" is clear (audience demographics, preferences, behavior patterns, engagement quality across four platforms), but there is no "Use when..." clause or any equivalent explicit trigger guidance, which caps completeness at 3 per the rubric guideline. Not 4 because the "when" is entirely missing rather than under-specified; not 2 because the "what" is concrete.

Trigger Term Quality

Natural user phrases like "audience demographics", "engagement quality", and the platform names "Facebook, Instagram, YouTube, and TikTok" give good keyword coverage. Not 5 because common variations users would say — "followers", "social media analytics", "Apify" — are absent; not 3 because coverage is broader than a couple of generic keywords.

Distinctiveness Conflict Risk

"Audience demographics ... across Facebook, Instagram, YouTube, and TikTok" carves a clear niche with platform-named triggers, so it is unlikely to fire for unrelated skills. Not 5 because it could still overlap with general social-media analytics or scraping skills; not 3 because the four named platforms plus audience/demographics framing is fairly specific.