canslim-screener

Screen US stocks using William O'Neil's CANSLIM growth stock methodology. Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum following O'Neil's investment system.

Quality

73%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/canslim-screener/SKILL.md

Quality

Content

60%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 content is actionable with concrete commands, a clear sequenced workflow, and well-organized one-level-deep references, but it suffers from heavy duplication and verbosity that inflate the token budget well beyond what the guidance earns.

Suggestions

Deduplicate the body: prerequisites, rating bands, component weights, the Finviz-fallback explanation, and the report-structure each currently appear 2-4 times — keep a single canonical version and link to it.

Move the full report template (Step 6) and the troubleshooting catalog into reference files, leaving SKILL.md as a lean overview with the script-invocation commands and the 6-step sequence.

Remove promotional padding ("proven methodology", "100% coverage", repeated Phase 3 status boxes) and consolidate the overview so every remaining token earns its place.

Dimension	Reasoning	Score
Conciseness	The 671-line body duplicates material extensively: prerequisites appear twice, rating bands and Finviz fallback are explained 3-4 times each, component weights are listed repeatedly, and the report structure is detailed in three places, with promotional padding ("proven methodology", "100% coverage").	2 / 5
Actionability	Provides concrete executable commands and flags ("python3 screen_canslim.py --api-key $FMP_API_KEY --max-candidates 40 --top 20", "--rs-benchmark SPY", "--disable-rs", "pip install requests beautifulsoup4 lxml") plus a full report template and component scoring tables, with only minor gaps (no inline Python examples).	4 / 5
Workflow Clarity	Steps 1-6 are clearly sequenced with validation checkpoints (API access verification, bear-market M=0 gating, 429 retry handling, graceful degradation with warnings), though checkpoints are scattered rather than consolidated into an explicit validate-fix-retry checklist.	4 / 5
Progressive Disclosure	Bundle is well-structured: 4 reference files (all verified to exist) and calculators are clearly signaled one level deep with per-file descriptions and a "How to Use References" section, though the SKILL.md itself remains monolithically long with inlined content (full report template, full troubleshooting) that could be split out.	4 / 5
	Total	14 / 20 Passed

Description

87%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 strong: it clearly states the capability, provides explicit trigger guidance with natural phrasing, and occupies a distinct niche (CANSLIM/O'Neil). Minor improvements would add synonyms and explicitly mention ranking/reporting outputs.

Dimension	Reasoning	Score
Specificity	Names the domain and a concrete action ("Screen US stocks using William O'Neil's CANSLIM growth stock methodology", "find stocks with strong earnings and price momentum") with several specific actions, though it does not enumerate ranking/scoring/reporting actions explicitly.	4 / 5
Completeness	Explicitly answers both what ("Screen US stocks using...CANSLIM growth stock methodology") and when ("Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum") with concrete trigger phrases.	5 / 5
Trigger Term Quality	Includes strong natural phrases users would say ("CANSLIM stock screening", "growth stock analysis", "momentum stock identification", "strong earnings and price momentum"), but misses some synonyms and variations of O'Neil/IBD terminology.	4 / 5
Distinctiveness Conflict Risk	Targets a clearly named, distinctive methodology ("William O'Neil's CANSLIM growth stock methodology", "O'Neil's investment system") with minimal overlap risk against other screener skills.	5 / 5
	Total	18 / 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 (672 lines); consider splitting into references/ and linking	Warning

	Total	15 / 16 Passed

Repository: tradermonty/claude-trading-skills
Path: skills/canslim-screener/SKILL.md
Commit: 3930d34

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.