SKILLEMALL.ai

BC ghostshield

反同事蒸馏防护盾 - 保护你的代码风格,防止被 AI 精准蒸馏。 提供三级混淆模型:基础防护、深度混淆、极致隐匿。

Not recommendedcritical or high security findings
ClawHub Agent Skills author: 13770626440 v1.0.0 MIT-0 11 files body ≈ 1 522 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
76/100
safety, quality, tests
Safety 60%
81
Quality 40%
68
Run on models
none yet
Process rating
C
51/100
Has gaps
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

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Obfuscation
If you install

The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

  • high Obfuscation uni-zero-width README.md:162
    Zero-width / invisible characters (possible hidden text) (4 occurrences)
    # Watermark: GS-2…500␀␀␀␀
Medium and low: 1
  • low Obfuscation uni-zero-width ghostshield/obfuscator.py:311
    Zero-width / invisible characters (possible hidden text) (26 occurrences) (detector / deny-list definition)
    # Zero-width markers: ␀␀␀␀␀␀␀␀␀␀␀␀␀␀␀␀␀␀␀␀
    detector

Files scanned: 11. 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")

Process rating: all ten parameters 51/100

  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 61 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1522 tokens
  • low 12 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 57: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 61 items
  • +4Has examples (4 code blocks)
  • +1License stated

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

External checks

ClawHub: clean
GhostShield is a local repository obfuscation tool with disclosed, user-triggered file rewriting and watermark features, but users should run it only on copies and review the output.
LLM: benign (high) · VirusTotal: · 29 May 2026