SKILLEMALL.ai

AB cmcc-credential

Handle China Mobile Digital Credential authorization flow for sensitive operations. This skill operates in three distinct phases: (1) Credential Loading - Parse and store credentials (appId, appKey) from user-provided files into memory without making any API calls, (1.5) Agent Binding - Bind agent using appName and appId before authorization, and (2) Sensitive Operation Authorization - When user attempts sensitive actions (deleting data, accessing secrets, viewing keys), request authorization, provide authorization link, poll status (5s interval, 10min timeout), and verify authorization before proceeding. Signature uses sorted JSON with HmacSHA256; encryption uses AES/ECB/PKCS5Padding with MD5(appKey) as key.

ClawHub Agent Skills author: RiceanKim v1.0.0 MIT-0 6 files body ≈ 3 621 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 67/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting

IntegrationAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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: 6. 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 2, column 14: description: Handle China Mobile Digital Credential authorization flow for sens… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 67/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 128 steps, 2 vague phrases
    • 100Tools and files. No external tools needed
    • 100Failures and branches. 6 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3621 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 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 718: enough signal without eating the budget
    • +4Structure: 47 headings
    • +3Step-by-step instructions: 128 items
    • +4Has examples (30 code blocks)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

    External checks

    ClawHub: suspicious
    This skill is coherent for CMCC authorization, but it stores and can expose reusable app credentials and phone-number data in ways users should review before installing.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026