SKILLEMALL.ai

BF kimi-quota-monitor

Kimi (Kimi Chat) membership quota monitoring and daily reporting. Use when the user needs to (1) check current Kimi usage percentage, (2) set up or configure automated Kimi quota daily push to WeChat via openclaw, (3) calculate quota period cycles and KimiClaw sandbox deduction logic, or (4) troubleshoot Kimi quota fetching failures. Triggers on phrases like "Kimi额度", "quota日报", "会员额度", "额度监控".

ClawHub Agent Skills author: SHAWNTRIBBIANI v1.0.0 MIT-0 4 files body ≈ 629 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process F 39/100 · Will not run — References files that are not bundled: references/quota_rules.md, scripts/fetch_quota.py

ProcedureSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
95
Quality 40%
80
Run on models
none yet
Process rating
F
39/100
Will not run
References files that are not bundled: references/quota_rules.md, scripts/fetch_quota.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Exfiltration intent-browser-credential-store skill-card.md:36
    Accesses a browser credential / cookie store (documentation of a security skill)
    **Other Properties Related to Output:** [Requires user-provided Kimi cookies, localStorage tokens, Chrome or Chromium, Playwright, and OpenClaw WeChat configuration before execution.] <br>
    security skill

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/quota_rules.md
  • warning missing-ref reference to a missing file: scripts/fetch_quota.py

Process rating: all ten parameters 39/100

Will not run. References files that are not bundled: references/quota_rules.md, scripts/fetch_quota.py
  • 0Tools and files. 2 referenced file(s) missing: references/quota_rules.md, scripts/fetch_quota.py
  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 629 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

  • +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
  • +5Description quotes 2 example trigger phrases
  • +3Description length 397: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
This quota-monitoring skill appears purpose-aligned, but it asks users to handle live Kimi session credentials in plaintext and can run recurring reports to WeChat.
LLM: suspicious (high) · VirusTotal: · 29 May 2026