edge-signal-aggregator

Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.

Quality

62%

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Securityby

Low

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Quality

Content

61%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 well-structured and action-oriented with concrete CLI commands and a clear resource map, but it is held back by a missing validation checkpoint in a batch workflow and by verbose inlined output examples. Tightening the examples and adding an explicit verify step would raise the weakest dimensions.

Suggestions

Add an explicit validation/verification checkpoint to the workflow, e.g. after running the aggregator, confirm the report was written and spot-check the contradiction and dedup counts before acting on signals.

Move the full JSON and markdown output schemas into a reference file (e.g. references/output-format.md) and keep only a compact representative excerpt inline to improve conciseness and progressive disclosure.

Remove or generalize the hardcoded timestamp ('2026-03-02T07:00:00Z') in the example, or relocate time-sensitive values to a clearly marked section, to avoid penalizing conciseness.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient and avoids explaining basics Claude already knows, but it inlines both a full ~75-line JSON example and a full markdown example and includes a time-sensitive timestamp ('2026-03-02T07:00:00Z') outside any deprecated section, so it could be tightened.	3 / 5
Actionability	Provides copy-paste-ready CLI invocations with real script paths and flags covering the basic run, custom weights, and min-conviction filtering cases; minor gaps (no sample upstream input shape) keep it just below a 5.	4 / 5
Workflow Clarity	The four steps (Gather → Run → Review → Act) are clearly sequenced, but this batch aggregation operation has no explicit validation or error-recovery checkpoint, which caps workflow clarity at 3 per the rubric.	3 / 5
Progressive Disclosure	Good structure with a Resources section clearly signaling real one-level-deep bundle files (scripts/aggregate_signals.py, references/signal-weighting-framework.md, assets/default_weights.yaml); the main gap is the large inlined output-format examples that could live in a reference file.	4 / 5
	Total	14 / 20 Passed

Description

63%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 and action-oriented with a clear niche, but it omits any explicit 'when to use' trigger guidance and relies on domain jargon rather than natural user phrasing. Adding a 'Use when...' clause with everyday trigger terms would lift completeness and trigger_term_quality.

Suggestions

Append a 'Use when...' clause with natural trigger phrases, e.g. 'Use when combining outputs from multiple edge-finding skills into a ranked dashboard or when reconciling conflicting signals across skills.'

Add user-facing synonyms and concrete artifact terms (e.g. 'edge ideas', 'signal shortlist', conviction scoring') alongside the technical jargon to improve trigger_term_quality.

Consider mentioning the input/output formats (JSON/YAML reports) to further distinguish the skill and ground the trigger terms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Aggregate and rank signals', 'weighted scoring, deduplication, and contradiction detection' — into a 'prioritized conviction dashboard', giving comprehensive coverage of capabilities.	5 / 5
Completeness	The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the rubric guidelines.	3 / 5
Trigger Term Quality	Relevant domain keywords ('signals', 'edge-finding skills', 'rank', 'conviction dashboard') are present but it leans on specialized jargon and misses natural user phrasing variations, synonyms, or file extensions.	3 / 5
Distinctiveness Conflict Risk	Naming specific upstream skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) carves a clear niche with only minor overlap risk against other edge-related skills; not a 5 because no explicit distinct trigger phrases are given.	4 / 5
	Total	15 / 20 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/edge-signal-aggregator/SKILL.md
Commit: 51c7907

Reviewed: 3 days ago

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