SKILLEMALL.ai

BD Bank Market Research Assistant

AI-powered market research and competitive intelligence assistant for banks - analyze industries, competitors, market trends, and generate structured market intelligence reports. Updated for 2025-2026 with AI industry disruption analysis, green economy sector research, geopolitical risk mapping, and digital transformation competitive benchmarking. Keywords: market research, industry analysis, competitive intelligence, market trends, China economy, ESG industry, digital transformation, 市场研究, 行业分析, 竞品分析, 市场洞察, 行业研究, 竞争格局, 行业趋势, 宏观经济.

ClawHub Agent Skills author: lingfeng-19 v5.0.2 MIT-0 2 files body ≈ 2 777 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
55
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: AI-powered market research and competitive intelligence assistant … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 49/100

  • 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 (Bank Market Research Assistant) differs from the folder (bank-market-research)
  • 100Tools and files. No external tools needed
  • 100Steps. 42 steps
  • 100Execution cost. Instruction body is 2777 tokens
  • 100Running it twice. No mutating operations
  • low 16 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 537: enough signal without eating the budget
  • +4Structure: 46 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: clean
This is a disclosed, text-only banking market research skill that provides analysis templates and compliance reminders rather than executing code or accessing systems.
LLM: benign (high) · VirusTotal: · 9 Sept 2026