SKILLEMALL.ai

BB github-personal-repo-publisher

Create a repository under your own GitHub account, wire a local project repo to it, and push committed history safely. 为你自己的 GitHub 账户创建仓库,把本地项目仓库接过去,并安全推送已提交历史。

ClawHub Agent Skills author: grey0758 v1.0.0 MIT-0 7 files body ≈ 759 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 69/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting

GeneratorGitHubSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
94
Quality 40%
76
Run on models
none yet
Process rating
B
69/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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. 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

✓ No critical or high findings

Medium and low: 2
  • medium Exfiltration exfil-send-secrets-to-url SKILL.md:71
    Instruction to send secrets/history to an external endpoint (describes API authentication (bearer / header / HTTPS); destination is a well-known publishing service)
    curl -fsSL -X POST -H 'Accept: application/vnd.github+json' -H "Authorization: Bearer $TOKEN" https://api.github.com/user/repos -d '{"name":"your-repo","private":true}'
    API authknown service
  • low Exfiltration net-credential-use SKILL.md:71
    Credential used in a network call (verify the destination is the intended service) (destination is a well-known publishing service)
    curl -fsSL -X POST -H 'Accept: application/vnd.github+json' -H "Authorization: Bearer $TOKEN" https://api.github.com/user/repos -d '{"name":"your-repo","private":true}'
    known service

Files scanned: 7. 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 69/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Failures and branches. 5 branches
  • 100Tools and files. No external tools needed
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 759 tokens
  • 100Running it twice. Mutating operations check current state

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)
  • +2Single-language instructions
  • +3Description length 161: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 33 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This is a disclosed GitHub publishing workflow with sensitive but purpose-aligned repo, remote, push, and token use.
LLM: benign (high) · VirusTotal: · 29 May 2026