SKILLEMALL.ai

BC remind-me

Create, list, and cancel reminders and cron jobs scoped to the channel they were requested from. Use when: user says 'remind me', 'set an alarm', 'schedule a cron', 'alert me when', 'every day at X do Y', 'cancel my reminder', 'list my reminders'. Auto-detects source channel, chat ID, and user timezone. Delivers back to originating chat. Asks for clarification if schedule or intent is ambiguous before creating anything.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: youpele52 v0.1.1 MIT-0 7 files body ≈ 3 324 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice

GeneratorTelegramWriting and documentsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
82
Quality 40%
85
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Running it twice w 4
30
Consistency w 8
40
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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

  • high Concealment en-hide-from-user SKILL.md:70
    Instruction to hide actions from the user
    - If tier 2 applies → use it silently, do not mention it to the user

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 63/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 14 mutating operations with no state check
  • 40Consistency. Frontmatter name (remind-me) differs from the folder (remind-me-pro)
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 82 steps
  • 100Failures and branches. 7 branches, has a failure section
  • 100Execution cost. Instruction body is 3324 tokens
  • 100Progress reporting. Reports progress
  • 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
  • low The response is described with custom markup (8 tags): a typed call is more reliable

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)
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 423: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 82 items
  • +3Output format is stated explicitly
  • +4Has examples (11 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

External checks

ClawHub: suspicious
This reminder skill is mostly purpose-aligned, but its cancel feature can delete reminders without verifying they belong to the current chat.
LLM: suspicious (high) · VirusTotal: · 28 May 2026