BF avalanche-analytics
Avalanche (AVAX) 生态综合分析工具。提供 Avalanche 子网架构分析、DeFi 协议监控、项目评估、子网生态追踪和投资机会发现。当用户需要分析 Avalanche 生态、评估 AVAX 项目、监控子网发展或获取雪崩链情报时触发此 Skill。
As a process F 31/100 · Will not run — References files that are not bundled: references/protocol-database.md, references/chain-metrics.md, references/subnet-guide.md
ReferenceInfrastructureData and analyticstype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
For the model run — optional
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: references/protocol-database.md - warning
missing-refreference to a missing file: references/chain-metrics.md - warning
missing-refreference to a missing file: references/subnet-guide.md - warning
missing-refreference to a missing file: scripts/subnet_analyzer.py - warning
missing-refreference to a missing file: scripts/project_evaluator.py - warning
missing-refreference to a missing file: scripts/validator_calculator.py
Process rating: all ten parameters 31/100
Will not run. References files that are not bundled: references/protocol-database.md, references/chain-metrics.md, references/subnet-guide.md
- 0Tools and files. 6 referenced file(s) missing: references/protocol-database.md, references/chain-metrics.md, references/subnet-guide.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (avalanche-analytics) differs from the folder (shenmeng-avalanche-analytics)
- 100Steps. 95 steps
- 100Execution cost. Instruction body is 1573 tokens
- 100Running it twice. No mutating operations
- low 14 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 132: enough signal without eating the budget
- +4Structure: 53 headings
- +3Step-by-step instructions: 95 items
- +4Has examples (13 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.
External checks
ClawHub: suspicious
The skill is mainly an Avalanche analytics helper, but it includes under-disclosed payment verification code that can send wallet/payment data to SkillPay and exposes a payment API key.
LLM: suspicious (high) · 28 May 2026