SKILLEMALL.ai

DF tourism-guide-harvester

(no description)

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: whhh1994 v1.5.0 MIT-0 4 files · 1 script body ≈ 5 580 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 28/100 · Will not run — References files that are not bundled: url, 有效分享链接

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
D
49/100
safety, quality, tests
Safety 60%
82
Quality 40%
0
Run on models
none yet
Process rating
F
28/100
Will not run
References files that are not bundled: url, 有效分享链接
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
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.

Exfiltration
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. 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. Add a description to the frontmatter: without it the skill never triggers.
  3. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  4. 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 Exfiltration exfil-secret-in-url scripts/start-tourism-guide.sh:106
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service)
    - 搜索URL: https://www.xiaohongshu.com/search_result?keyword=… -c "import urllib.parse; print(urllib.parse.quote('$DEST'))")&type=note&sort=collect_count

Files scanned: 4. 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 ≈ 5580 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: url
  • warning missing-ref reference to a missing file: 有效分享链接

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: url, 有效分享链接
  • 0Tools and files. 2 referenced file(s) missing: url, 有效分享链接
  • 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. 3 mutating operations with no state check
  • 70Execution cost. Instruction body is 5580 tokens
  • 100Steps. 139 steps
  • 100Consistency. Name and required fields are in place
  • low 36 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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -283 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 120 headings
  • +3Step-by-step instructions: 139 items
  • +4Has examples (38 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: suspicious
The skill does what it claims, but it can control a logged-in browser and persist scraped content with limited safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026