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CF Molt Trader Skill

Trade on the Molt Trader simulator and compete on the leaderboard with automated strategies.

modbender/skill-library-mcp Agent Skills author: modbender MIT 12 files body ≈ 1 485 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Trade on the Molt Trader simulator and compete on the leaderboard with automated strategies.

As a process F 33/100 · Will not run — References files that are not bundled: CONTRIBUTING.md

IntegrationSoftware developmenttype 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%
85
Quality 40%
56
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: CONTRIBUTING.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.

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 text references files that are not there: add them or drop the references.
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 · 7

✓ No critical or high findings

Medium and low: 7
  • medium Exfiltration net-redirectable-api-key src/examples/momentum-trader.ts:63
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • medium Exfiltration net-redirectable-api-key src/examples/test-connection.ts:22
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • low Secrets in code secret-high-entropy-token package-lock.json:81
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…cjV+2Z+GK+EEY7…R4x+N3TA…nIr+TMcC…z6Q==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:153
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-oGB+Uxlg…BKZ+GTy0…lih/NSHS…cSg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:180
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…4bN+9AEq…ThG+YCEm…t1S+zGED…1zq/mg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:234
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…JbG+vnnQ…1TK+nxAp…hhm+kzE4…g4g==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:302
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…vZS+VIDU…jX4+qx9M…saQ==",
    detector

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

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: CONTRIBUTING.md

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: CONTRIBUTING.md
  • 0Tools and files. 1 referenced file(s) missing: CONTRIBUTING.md
  • 0Result and completion. Does not say what the result is
  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (Molt Trader Skill) differs from the folder (molt-trader-skill)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 21 steps
  • 100Execution cost. Instruction body is 1485 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 92: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (14 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.