SKILLEMALL.ai

BD Bank Credit Memo Writer

AI-powered bank credit memo and credit analysis report writer - generate structured credit analysis reports, credit ratings, and facility recommendations. Updated for 2024-2026 Basel III risk weight framework, ESG/green credit assessment, real estate "whitelist" policy, and digital supply chain finance. Keywords: credit memo, credit analysis, credit rating, loan approval, Basel III, ESG credit, China banking, 信用备忘录, 授信报告, 信用分析报告, 评级报告, 信贷审批, 贷款评估, 额度测算, 担保评估.

ClawHub Agent Skills author: lingfeng-19 v4.1.1 MIT-0 4 files body ≈ 1 899 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 46/100 · 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
46/100
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: 4. 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 bank credit memo and credit analysis report writer - ge… ^ ); 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 46/100

  • 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
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (Bank Credit Memo Writer) differs from the folder (bank-credit-memo)
  • 100Tools and files. No external tools needed
  • 100Steps. 29 steps
  • 100Execution cost. Instruction body is 1899 tokens

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 463: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
This is a documentation-only credit memo writing skill whose sensitive inputs are expected for its banking purpose, but users should handle real borrower data carefully.
LLM: benign (high) · VirusTotal: · 28 Jun 2026