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ClawHub Agent Skills author: Keddleman v5.1.0 MIT-0 6 files body ≈ 7 079 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process A 81/100 · Runs to the end — weak spots: running it twice

ProcedureInfrastructureSales and CRMtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
69/100
safety, quality, tests
Safety 60%
75
Quality 40%
61
Run on models
none yet
Process rating
A
81/100
Runs to the end
Running it twice w 4
30
When it triggers w 12
50
Result and completion w 14
60
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.
  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 SKILL.md:593
    Credential used in a network call (verify the destination is the intended service)
    curl -s -X POST "$ESSENTIALIST_API_URL/api/agent/tracks/{track_id}/activate" -H "X-API-Key: $ESSENTIALIST_API_KEY" | jq
  • medium Exfiltration net-credential-use SKILL.md:594
    Credential used in a network call (verify the destination is the intended service)
    curl -s -X POST "$ESSENTIALIST_API_URL/api/agent/tracks/{track_id}/pause" -H "X-API-Key: $ESSENTIALIST_API_KEY" | jq
  • medium Exfiltration net-credential-use SKILL.md:595
    Credential used in a network call (verify the destination is the intended service)
    curl -s -X POST "$ESSENTIALIST_API_URL/api/agent/tracks/{track_id}/resume" -H "X-API-Key: $ESSENTIALIST_API_KEY" | jq
  • medium Exfiltration net-credential-use SKILL.md:598
    Credential used in a network call (verify the destination is the intended service)
    curl -s "$ESSENTIALIST_API_URL/api/projects/{id}/contacts/by-stage?stage=qualified" -H "X-API-Key: $ESSENTIALIST_API_KEY" | jq
  • medium Exfiltration net-credential-use SKILL.md:599
    Credential used in a network call (verify the destination is the intended service)
    curl -s -X PATCH "$ESSENTIALIST_API_URL/api/projects/{id}/contacts/{cid}/stage" -H "X-API-Key: $ESSENTIALIST_API_KEY" -H "Content-Type: application/json" -d '{"stage":"won"}' | jq

Files scanned: 6. 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 ≈ 7079 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 81/100

  • 30Running it twice. 52 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 7079 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 132 steps
  • 100Failures and branches. 21 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 27 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)
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 316: enough signal without eating the budget
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 132 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
This is a real sales-automation skill, but it pushes agents toward account setup and outbound email actions without clear user approval boundaries.
LLM: suspicious (high) · VirusTotal: · 29 May 2026