SKILLEMALL.ai

DD myapp-creator

(no description)

Not recommendedlow grade D
ClawHub Agent Skills author: zhang6714268 v1.0.31 MIT-0 40 files · 6 scripts body ≈ 6 701 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
D
57/100
safety, quality, tests
Safety 60%
95
Quality 40%
0
Run on models
none yet
Process rating
D
39/100
Unfinished process
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
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. Add a description to the frontmatter: without it the skill never triggers.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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

✓ No critical or high findings

Medium and low: 1
  • medium Exfiltration net-credential-use scripts/_common.sh:19
    Credential used in a network call (verify the destination is the intended service)
    CURL_OPTS=(-sS --connect-timeout 5 --max-time "${MYAPP_CURL_MAX_TIME}" -H "X-MYAPP-TOKEN: ${MYAPP_API_TOKEN}" -H "Content-Type: application/json")

Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger
  • warning body-long SKILL.md body ≈ 6701 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 39/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 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
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6701 tokens
  • 100Steps. 188 steps
  • 100Consistency. Name and required fields are in place
  • low The response is described with custom markup (17 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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -215 emoji in the instructions: noise for the model
  • -35 of 5 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 188 items
  • +4Has examples (12 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: suspicious
This looks like a legitimate app-creation integration, but it uploads user content and identifiers to a backend and stores a long-lived local token with limited user-facing control described.
LLM: suspicious (medium) · VirusTotal: · 28 May 2026