SKILLEMALL.ai

CD promotion-apply-skills

灵渠 Banner 推广创建、查询、复制、修改、状态修改、创意和关联物料 skill。用户说“配置发现页 banner”“帮我配置发现页banner”“查询/复制/创建/预占/取消预占/状态修改/修改/配置 banner 推广/素材”时使用。

ClawHub Agent Skills author: CIO v1.0.11 MIT-0 12 files body ≈ 12 469 tokens Open the sourceclawhub.ai analyzed 2 d ago

灵渠 Banner 推广创建、查询、复制、修改、状态修改、创意和关联物料 skill。用户说“配置发现页 banner”“帮我配置发现页banner”“查询/复制/创建/预占/取消预占/状态修改/修改/配置 banner 推广/素材”时使用。

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
C
72/100
safety, quality, tests
Safety 60%
75
Quality 40%
68
Run on models
none yet
Process rating
D
43/100
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

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.

Dangerous commands 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 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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  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 · 5

✓ No critical or high findings

Medium and low: 5
  • medium Exfiltration net-credential-use references/image-upload-nos.md:126
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST "https://nosu…net/${BUCKET}/${OBJECT_KEY}?offset=0&complete=true&version=1.0" \
  • medium Dangerous commands cmd-eval-dynamic scripts/resize_cover.py:17
    Dynamic code execution from decoded/untrusted input
    os.system(f"{sys.executable} -m pip install Pillow requests -q")
  • medium Dangerous commands cmd-eval-dynamic scripts/resize_cover.py:24
    Dynamic code execution from decoded/untrusted input
    os.system(f"{sys.executable} -m pip install requests -q")
  • medium Dangerous commands cmd-eval-dynamic scripts/validate_image_size.py:16
    Dynamic code execution from decoded/untrusted input
    os.system(f"{sys.executable} -m pip install Pillow -q")
  • medium Dangerous commands cmd-eval-dynamic scripts/validate_image_size.py:26
    Dynamic code execution from decoded/untrusted input
    os.system(f"{sys.executable} -m pip install requests -q")

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 12469 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 43/100

  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Execution cost. Instruction body is 12469 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 175 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • low 19 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -32 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 121: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 175 items
  • +4Has examples (45 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
This skill is mostly aligned with managing banner promotions, but it needs Review because it can change real promotion/admin state and its helper scripts can automatically install packages while processing images.
LLM: suspicious (high) · VirusTotal: · 23 Jun 2026