SKILLEMALL.ai

BF newsletter-curation

Newsletter curation with content sourcing, editorial structure, and subscriber growth strategies. Covers issue formatting, link roundups, commentary style, and sending cadence. Use for: email newsletters, link roundups, weekly digests, curated content, creator newsletters. Triggers: newsletter, email newsletter, newsletter curation, weekly digest, link roundup, curated newsletter, newsletter writing, newsletter format, subscriber growth, newsletter strategy, content curation, newsletter template

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Ömer Karışman v0.1.5 2 files body ≈ 2 255 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process F 18/100 · Will not run — References files that are not bundled: url

GeneratorWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
79/100
safety, quality, tests
Safety 60%
82
Quality 40%
75
Run on models
none yet
Process rating
F
18/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Steps w 15
0
Result and completion w 14
0
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.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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.
  2. 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

  • high Dangerous commands cmd-pipe-to-shell SKILL.md:14
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://cli.inference.sh | sh && infsh login

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: url

Process rating: all ten parameters 18/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 0Steps. Prose only: no discrete steps
  • 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
  • 30Running it twice. 6 mutating operations with no state check
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2255 tokens
  • low 11 top-level sections: this looks like several domains in one skill

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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 500: enough signal without eating the budget
  • +4Structure: 23 headings
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
The skill’s newsletter guidance is coherent, but its install and related-skill commands rely on mutable remote code paths that users should review before installing.
LLM: suspicious (high) · VirusTotal: suspicious · 10 Sept 2026