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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.

60

Quality

70%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/edge-signal-aggregator/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%

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

The content is highly actionable with executable commands and a well-organized bundle structure, but it is somewhat verbose due to redundant report examples and lacks validation checkpoints in its batch workflow.

Suggestions

Collapse the JSON and Markdown report examples into one canonical example plus a short note describing the other format, to reduce token cost.

Add an explicit validation/feedback step in the workflow (e.g. verify upstream report files exist before running, and re-run or inspect the dedup log if contradictions exceed a threshold).

DimensionReasoningScore

Conciseness

The body is mostly efficient and domain-specific, but the full JSON and Markdown report examples largely duplicate each other; trimming one would tighten the document without losing the output contract.

2 / 3

Actionability

Provides copy-paste-ready CLI invocations with concrete flags and paths plus a complete output JSON schema, matching the fully-executable anchor.

3 / 3

Workflow Clarity

The four steps (Gather, Run, Review, Act) are clearly sequenced, but this batch aggregation has no validation/feedback checkpoint (e.g. verify inputs exist, re-run on error), which caps it at 2.

2 / 3

Progressive Disclosure

A Resources section signals one-level-deep references to scripts/aggregate_signals.py, references/signal-weighting-framework.md, and assets/default_weights.yaml — all real bundle files — giving clear navigation.

3 / 3

Total

10

/

12

Passed

Description

67%

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 distinctive, clearly naming the upstream skills and concrete aggregation actions. Its main weakness is the missing explicit 'when to use' trigger guidance, which caps completeness.

Suggestions

Add an explicit trigger clause, e.g. 'Use when consolidating outputs from multiple edge-finding skills into a ranked conviction shortlist.'

Include more natural user-facing phrasings (e.g. 'combine edge analyses', 'rank trading signals') alongside the domain jargon.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Aggregate and rank signals', 'weighted scoring, deduplication, and contradiction detection' — matching the score-3 anchor of several specific concrete actions.

3 / 3

Completeness

It clearly states what the skill does but has no 'Use when...' clause or equivalent explicit trigger guidance, which the guidelines cap at 2.

2 / 3

Trigger Term Quality

Terms like 'conviction dashboard' and 'edge-finding skills' are domain jargon rather than phrasings a user would naturally say; common natural variations ('combine my edge analyses', 'rank trading signals') are missing.

2 / 3

Distinctiveness Conflict Risk

Naming the four specific upstream skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) carves a clear niche unlikely to trigger the wrong skill.

3 / 3

Total

10

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
tradermonty/claude-trading-skills
Reviewed

Table of Contents

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