SKILLEMALL.ai

BD birthday-reminder

管理并计算生日提醒(阳历与农历),支持每条记录单独配置和全局默认值,支持当天提醒/提前 N 天/多次提醒和提醒时间配置,默认使用北京时间。用于需要生成或维护生日提醒方案、编写配置文件、验证提醒是否到期,并结合官方定时任务技能自动触发通知发送。

ClawHub Agent Skills author: Jeff v1.0.6 MIT-0 8 files body ≈ 838 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
94
Quality 40%
71
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

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. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Exfiltration exfil-webhook-url scripts/notify_bridge.py:116
    Webhook / callback URL commonly used for exfiltration (verify the destination) (quoted — discussed, not commanded)
    url = f"https://api.telegram.org/bot{token}/sendMessage"
    quoted
  • low Exfiltration exfil-webhook-url assets/notify.example.json:34
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    "webhook": "https://hooks.slack.com/services/xxxx"
    placeholder

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

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 (birthday-reminder) differs from the folder (birthday-reminder-cn)
  • 100Tools and files. No external tools needed
  • 100Steps. 37 steps
  • 100Execution cost. Instruction body is 838 tokens
  • 100Running it twice. No mutating operations

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
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 121: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (10 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
This is a coherent birthday reminder skill that can send configured notifications, so users should protect reminder data and tokens but the behavior is disclosed and purpose-aligned.
LLM: benign (high) · VirusTotal: · 29 May 2026