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onchain-analysis

On-chain data analysis — active addresses / whale tracking / TVL / DEX liquidity, interpretation and signal generation using on-chain valuation metrics such as MVRV / NVT / SOPR.

57

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./agent/src/skills/onchain-analysis/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%

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

The body is a well-structured, information-rich reference with explicit thresholds and a usable report template, but it is monolithic, omits the executable data-acquisition step, and frames the analysis workflow only implicitly. Splitting reference material into bundle files and adding an explicit step-by-step procedure would lift the weaker dimensions.

Suggestions

Add a short executable example for fetching on-chain data (e.g., a Glassnode/Nansen API call) so the analysis pipeline is actionable end-to-end, not just thresholds.

Pull the detailed historical-reference tables and per-metric deep dives into separate reference files (e.g., references/metrics.md, references/history.md) and link them from SKILL.md to improve progressive disclosure.

Add an explicit numbered "Analysis procedure" section (gather snapshot → score per dimension → cross-check whale/capital flow → write report) with a verification checkpoint confirming data freshness before concluding.

DimensionReasoningScore

Conciseness

The body is dense, mostly non-redundant reference data, but it runs ~250 lines and includes some removable hand-holding ("Simply put: on average, are the coins sold today being sold at a profit or a loss?", "Similar to a PE ratio") and speculative historical tables that could be trimmed.

2 / 3

Actionability

It provides concrete thresholds, formulas, and a copy-paste report template, but the actual data-acquisition step is missing — it only names external APIs (Glassnode/Nansen) without any executable call, leaving a key detail incomplete.

2 / 3

Workflow Clarity

The composite-scoring framework and output template imply a sequence (collect metrics → score → report), but the analysis is never laid out as explicit numbered steps with checkpoints; for a multi-step analytical workflow the sequence stays implicit.

2 / 3

Progressive Disclosure

Sections are well-organized, but everything is in one monolithic SKILL.md with no bundle files (references/scripts/assets absent) and no pointers to separate references, so content that could be split (historical tables, per-metric deep-dives) is inline.

2 / 3

Total

8

/

12

Passed

Description

82%

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 specific, well-anchored description with strong trigger terms and a clear niche, but it lacks any explicit "Use when…" guidance telling Claude when to invoke the skill. Adding a usage trigger clause would raise completeness to the top level.

Suggestions

Append an explicit trigger clause, e.g. "Use when analyzing on-chain blockchain data, tracking whale flows, assessing DeFi/TVL liquidity, or valuing BTC/ETH via MVRV/NVT/SOPR."

Clarify which chains/assets the skill targets (BTC/ETH) in the description so Claude knows its scope before reading the body.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete capabilities and metrics — "active addresses / whale tracking / TVL / DEX liquidity, interpretation and signal generation" plus "MVRV / NVT / SOPR" — rather than vague language.

3 / 3

Completeness

It answers "what does this do" thoroughly but never provides a "Use when…" clause or equivalent explicit trigger guidance, so completeness is capped at 2 per the rubric guideline.

2 / 3

Trigger Term Quality

It surfaces natural terms a crypto analyst would actually say ("on-chain data analysis", "whale tracking", "TVL", "DEX liquidity", "MVRV", "NVT", "SOPR"), giving good coverage of likely user phrasings.

3 / 3

Distinctiveness Conflict Risk

The on-chain-analysis niche with named valuation metrics (MVRV/NVT/SOPR) is clearly distinct and unlikely to trigger for unrelated skills.

3 / 3

Total

11

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
HKUDS/Vibe-Trading
Reviewed

Table of Contents

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