earnings-calendar

This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. 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. The skill focuses on mid-cap and above companies (over $2B market cap) that have significant market impact, organizing the data by date and timing in a clean markdown table format. Supports multiple environments (CLI, Desktop, Web) with flexible API key management.

Quality

81%

Does it follow best practices?

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Securityby

High

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Quality

Content

70%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The skill is highly actionable with a clear, validated workflow, but it is heavily padded and inlines content that belongs in the bundled template file. Trimming redundant sections and externalizing the report template would materially improve it.

Suggestions

Replace the inlined ~100-line report template in Step 6 with a pointer to assets/earnings_report_template.md to avoid duplicating content already in the bundle.

Remove the redundant Security Notes section (lines 668-692) and Best Practices Do's/Don'ts list; the API-key handling is already covered in Step 3 and the troubleshooting section.

Condense the four Use Cases and the conceptual 'Why This Matters' notes, keeping only the concrete executable workflow steps.

Dimension	Reasoning	Score
Conciseness	The body is noticeably verbose: a ~100-line inlined report template duplicating the asset file, a Best Practices Do's/Don'ts list, and a Security Notes section that repeats Step 3's API-key warnings — several large padded sections beyond 'some' over-explanation.	2 / 5
Actionability	Provides copy-paste-ready, executable commands with real arguments (e.g. fetch_earnings_fmp.py with date args and API key passing), a concrete JSON output schema, and an error-code handling table covering the common CLI/Desktop/Web cases.	5 / 5
Workflow Clarity	Eight clearly sequenced steps include an explicit QA checklist (Step 7) with data-quality, completeness, and format checks plus error-recovery feedback in Step 4 (401/429/empty-result handling).	5 / 5
Progressive Disclosure	References are clearly signaled and the bundle (fmp_api_guide.md, two scripts, one template) is one level deep, but the entire report template is inlined in Step 6 instead of pointing to the existing assets/earnings_report_template.md — content that belongs in a separate file is inline.	3 / 5
	Total	15 / 20 Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, complete, and well-scoped, with an explicit 'Use this when' trigger clause and concrete capability statements in third person. It only slightly under-covers trigger synonyms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — retrieving earnings via FMP API, filtering by market cap (>$2B), organizing by date/timing, markdown table formatting, and multi-environment key management — giving comprehensive coverage of what the skill does.	5 / 5
Completeness	Clearly states both the 'what' (retrieves earnings announcements, organizes by date/timing in markdown) and an explicit 'Use this when...' clause with multiple concrete triggers, satisfying the top anchor.	5 / 5
Trigger Term Quality	Includes natural phrases users would say ('earnings calendar data', 'which companies are reporting earnings in the upcoming week', 'weekly earnings review'), but is missing several common synonyms like 'earnings report' or 'earnings this week', keeping it just below comprehensive.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (US-stock earnings calendar via FMP API with a >$2B market-cap filter) with distinct triggers, making overlap with other skills minimal.	5 / 5
	Total	19 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (722 lines); consider splitting into references/ and linking	Warning

	Total	15 / 16 Passed

Repository: tradermonty/claude-trading-skills
Path: examples/weekly-trade-strategy/skills/earnings-calendar/SKILL.md
Commit: 3930d34

Reviewed: 1 day ago

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