SKILLEMALL.ai

AD screen-activity-tracker

Screen activity tracking. Trigger: track screen activity, start/stop tracking, daily summary, search history, 开始追踪屏幕, 屏幕活动总结, 整理今天的操作. Uses cron tool for tracking and bash for summary/search.

ClawHub Agent Skills author: zeject v1.0.1 MIT-0 10 files · 2 scripts body ≈ 429 tokens Open the sourceclawhub.ai analyzed 34 h ago

Screen activity tracking.

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
D
44/100
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

    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: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 44/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 75Steps. 3 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 429 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (3 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)
    • +3Output format is not stated: the model decides each time
    • -31 of 3 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 191: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 3 items
    • +4Has examples (4 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: suspicious
    This screen-tracking skill does what it claims at a high level, but it records full-screen activity in the background and has under-disclosed privacy and data-transfer risks.
    LLM: suspicious (high) · VirusTotal: · 3 Jul 2026