SKILLEMALL.ai
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Connect to S2G (s2g.run) visual workflow automation platform over WebSocket. Execute workflow nodes as tools — password generators, hash functions, date math, format converters, database queries, knowledge base, and any custom node. Use when asked to run S2G workflows, execute S2G nodes, connect to S2G, manage S2G workflows, or interact with the S2G platform API.

modbender/skill-library-mcp Agent Skills author: modbender MIT 6 files body ≈ 2 596 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Connect to S2G (s2g.run) visual workflow automation platform over WebSocket. Execute workflow nodes as tools — password generators, hash functions, date math…

As a process C 57/100 · Has gaps — weak spots: when it triggers, failures and branches, consistency

IntegrationInfrastructuretype 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
73/100
safety, quality, tests
Safety 60%
60
Quality 40%
92
Run on models
none yet
Process rating
C
57/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Running it twice w 4
30
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

    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 · 8

    ✓ No critical or high findings

    Medium and low: 8
    • medium Exfiltration net-credential-use references/api.md:102
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "X-API-Key: $KEY" $BASE/workflows/{id} | python3 -c "
    • medium Exfiltration net-credential-use references/api.md:130
      Credential used in a network call (verify the destination is the intended service)
      curl -H "X-API-Key: $KEY" "$BASE/catalog/categories"
    • medium Exfiltration net-credential-use references/api.md:141
      Credential used in a network call (verify the destination is the intended service)
      curl -H "X-API-Key: $KEY" "$BASE/catalog/nodes/Cust…e64/schema"
    • medium Exfiltration net-credential-use references/api.md:172
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "X-API-Key: $KEY" $BASE/workflows/{id} | python3 -c "
    • medium Exfiltration net-credential-use references/api.md:178
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "X-API-Key: $KEY" "$BASE/catalog/nodes/$ntype/schema" | python3 -c "
    • medium Exfiltration net-credential-use SKILL.md:146
      Credential used in a network call (verify the destination is the intended service)
      curl -H "X-API-Key: $KEY" "https://s2g.run/api/v1/catalog/nodes/Cust…e64/schema"
    • medium Exfiltration net-credential-use SKILL.md:149
      Credential used in a network call (verify the destination is the intended service)
      curl -H "X-API-Key: $KEY" "https://s2g.run/api/v1/catalog/categories"
    • medium Exfiltration net-credential-use SKILL.md:152
      Credential used in a network call (verify the destination is the intended service)
      curl -H "X-API-Key: $KEY" "https://s2g.run/api/v1/catalog/categories/AI/nodes"

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 57/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 16 mutating operations with no state check
    • 40Consistency. Frontmatter name (s2g) differs from the folder (s2g-workflow-engine)
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 69 steps
    • 100Execution cost. Instruction body is 2596 tokens
    • 100Progress reporting. Reports progress
    • 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)
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 365: enough signal without eating the budget
    • +4Structure: 30 headings
    • +3Step-by-step instructions: 69 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.