Conciseness

At 721 lines the body is noticeably verbose: the full ~100-line report template is inlined despite assets/earnings_report_template.md existing, API-key instructions appear in four places (Prerequisites, Step 3.2.1, Security Notes, Best Practices), and the closing Summary restates the Overview. Not score 1 because most material is domain-specific rather than re-explaining concepts Claude already knows; not score 3 because the duplication and padding are extensive, not incidental.

Actionability

Fully executable throughout: exact commands with real date examples ('python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09'), real script paths, expected JSON output shape, per-error-code handling (401/429/empty/connection), a working one-liner, and a concrete manual fallback with URLs. Copy-paste ready and covers the common cases — a direct match to the top anchor.

Workflow Clarity

An 8-step clearly sequenced workflow with explicit validation (Step 7 QA checklist of data/completeness/format checks), feedback loops for error recovery (401 → verify/re-enter key, 429 → wait, empty → widen range), and a fallback mode with its own sub-workflow. Not score 4 because checkpoints are explicit and checklist-based, matching the top anchor; the operation is read-only retrieval plus report generation, so the destructive-operation cap does not apply.

Progressive Disclosure

References are well signaled and one level deep (Step 2 'Read: references/fmp_api_guide.md', script locations, 'Report Template: assets/earnings_report_template.md'), and all referenced bundle files exist. Not score 5 because the ~100-line report template and much of the API guidance summary are inlined in SKILL.md even though a separate template file and a 609-line reference already hold that content — content that should live in the bundle is duplicated in the body. Not score 3 because most content is appropriately placed and navigation is easy.

Specificity

Concrete actions are named ('retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API', 'organizing the data by date and timing in a clean markdown table format') but coverage is not comprehensive — the latter half describes scope (mid-cap and above, over $2B) and environments rather than listing additional actions. Not score 5 because it lists only two real actions; not score 3 because those actions are specific and supplemented by concrete detail (markdown table format, API source).

Completeness

Explicitly answers both what ('retrieves upcoming earnings announcements for US stocks using the FMP API... organizing the data by date and timing in a clean markdown table format') and when ('Use this when the user requests earnings calendar data, wants to know which companies are reporting earnings in the upcoming week, or needs a weekly earnings review') with concrete trigger phrases — a direct match to the top anchor.

Trigger Term Quality

Natural phrases users would say are present ('requests earnings calendar data', 'which companies are reporting earnings in the upcoming week', 'needs a weekly earnings review'). Not score 5 because common synonyms like 'earnings this week', 'who reports earnings', or 'earnings report' are missing; not score 3 because multiple natural trigger phrases are already covered.

Distinctiveness Conflict Risk

A clear niche (US stock earnings calendars, mid-cap+ via FMP API) with distinct trigger terms that are unlikely to fire for unrelated skills. Neither the score-4 anchor (minor overlap with closely related skills) nor below applies.