pead-screener

Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.

Quality

100%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

100%

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

A well-structured, actionable skill body: executable commands for both input modes, a clear four-step workflow with an embedded degradation feedback loop, and clean progressive disclosure to two real reference files. No padding or concept re-explanation.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence - no concept explanations, just headings, executable commands, and a focused pitfall note - so every token earns its place.	3 / 3
Actionability	Provides copy-paste-ready commands with real flags for both Mode A and Mode B (e.g. '--lookback-days 21 --watch-weeks 6 --min-gap 5.0') plus concrete decision thresholds in Step 4.	3 / 3
Workflow Clarity	A clearly sequenced four-step workflow with an explicit error-recovery feedback loop (the degraded-output pitfall: detect budget trimming / non-US symbols -> mark degraded -> manual review only).	3 / 3
Progressive Disclosure	SKILL.md is an overview that points to two real, one-level-deep reference files (pead_strategy.md, entry_exit_rules.md) via both inline 'Load' cues and a Resources section, with theory kept out of the body.	3 / 3
	Total	12 / 12 Passed

Description

100%

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

A concise, third-person description that names concrete actions, gives explicit use-when triggers, and occupies a clear niche. It cleanly satisfies every dimension with no fluff or over-claims.

Dimension	Reasoning	Score
Specificity	Names multiple concrete actions - 'Screen post-earnings gap-up stocks', 'Analyzes weekly candle formation to detect red candle pullbacks and breakout signals', and 'Supports two input modes' - matching the anchor for listing several specific concrete actions.	3 / 3
Completeness	Explicitly states what the skill does (screen for PEAD patterns via weekly candle analysis) and when to use it via an explicit 'Use when...' clause, satisfying both halves.	3 / 3
Trigger Term Quality	The 'Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups' clause covers natural phrasings a user would actually say.	3 / 3
Distinctiveness Conflict Risk	The PEAD / post-earnings-drift niche with its specific trigger terms is clearly distinct and unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: tradermonty/claude-trading-skills
Path: skills/pead-screener/SKILL.md
Commit: 62a1635

Reviewed: 5 days ago

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