SKILLEMALL.ai

AB megacmd

CLI agent for MEGA.nz. Activate when the user asks to upload files to MEGA, download from MEGA, sync local folders with MEGA cloud, schedule backups to MEGA, share files via MEGA public links, mount MEGA as a local folder (FUSE on Linux), serve files via MEGA WebDAV/FTP, or manage MEGA account settings.

ClawHub Agent Skills author: Alefsander Ribeiro v1.0.1 MIT-0 7 files body ≈ 4 214 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 67/100 · Nearly there — weak spots: result and completion

IntegrationAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Tools and files w 18
60
When it triggers w 12
70
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: 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 67/100

    • 0Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 5 branches
    • 70Execution cost. Instruction body is 4214 tokens
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 19 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (4 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
    • -226 emoji in the instructions: noise for the model
    • -42 reference files, but SKILL.md never points to them: the model will not open them
    • +2Single-language instructions
    • +3Description length 304: enough signal without eating the budget
    • +4Structure: 37 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (19 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: suspicious
    This MEGA cloud-storage skill appears purpose-aligned, but it gives an agent powerful delete, sync, sharing, credential, and public-serving capabilities without enough clear safety gates.
    LLM: suspicious (medium) · VirusTotal: · 14 Jun 2026