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emblem-market-research

Crypto market intelligence via EmblemAI. Trending tokens, on-chain analytics, derivatives data, and smart money tracking from CoinGecko, CoinGlass, Birdeye, and Nansen. Use when the user wants market data, trending tokens, derivatives analytics, or on-chain intelligence.

67

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

75%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 body is highly actionable with executable commands and a verified helper script, well-structured with clear sections, and the skill's read-only scope correctly avoids needing validation checkpoints. The main weakness is redundancy across three overlapping tables that inflates token use.

Suggestions

Consolidate the 'What This Skill Can Do', 'Data Sources', and 'Communication Tips' tables — they restate tools and examples already shown in Research Patterns; merge into one canonical tool/capability reference to cut tokens.

If the full tool inventory is valuable, move the per-source tool tables into a references/ file and keep only a concise capability summary inline, improving both conciseness and progressive_disclosure.

Add a one-line note near the Token Research workflow stating the steps are independent pick-and-choose queries (if intended) so the workflow intent is unambiguous.

DimensionReasoningScore

Conciseness

Mostly efficient with tables and command examples and no conceptual padding, but the capability table, Data Sources table, and Communication Tips table overlap significantly with Research Patterns, adding redundant tokens that could be tightened.

3 / 5

Actionability

Provides many fully executable, copy-paste-ready `emblemai` command examples covering common cases, plus a real runnable helper script (scripts/market-scan.sh, verified present).

5 / 5

Workflow Clarity

A clearly sequenced 4-step Token Research workflow (Discovery → Deep Dive → On-Chain Intelligence → Derivatives Context) with concrete commands; the read-only nature means validation checkpoints are not required, but it reads more as a menu of patterns than a single tightly-sequenced process with explicit checkpoints.

4 / 5

Progressive Disclosure

Well-organized into clear sections with a one-level-deep, clearly signaled reference to the helper script; the large capability and data-source tables could arguably live in a separate reference file, keeping it just short of a 5.

4 / 5

Total

16

/

20

Passed

Description

86%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, uses third person, and clearly pairs a 'what' statement with an explicit 'Use when...' trigger clause covering concrete user intents. Its only weakness is trigger-term coverage missing a few natural synonyms.

DimensionReasoningScore

Specificity

Names the domain plus several concrete actions ('Trending tokens', 'on-chain analytics', 'derivatives data', 'smart money tracking') and specific data sources, with only minor gaps; not a 5 because the actions are data-category labels rather than fully concrete verbs.

4 / 5

Completeness

Explicitly answers both what ('Crypto market intelligence... Trending tokens, on-chain analytics, derivatives data, and smart money tracking') and when ('Use when the user wants market data, trending tokens, derivatives analytics, or on-chain intelligence.') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural trigger phrases a user would say ('market data, trending tokens, derivatives analytics, or on-chain intelligence'), but is missing common synonyms such as 'crypto prices' or 'what's pumping'.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (crypto market intelligence via named providers CoinGecko/CoinGlass/Birdeye/Nansen) with distinct triggers, giving minimal conflict risk with other skills.

5 / 5

Total

18

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
EmblemCompany/Agent-skills
Reviewed

Table of Contents

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