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CC storyclaw-polymarket-trading

Self-evolving Polymarket trading bot. Design strategy with user, run paper trading, auto-improve until edge target met, then ask to switch to live.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Parker v0.1.0 MIT-0 10 files body ≈ 1 295 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
64/100
safety, quality, tests
Safety 60%
60
Quality 40%
69
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 6

  • high Dangerous commands cmd-persistence SKILL.md:98
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null; echo "*/15 * * * * USER_ID=$TELEGRAM_USER_ID python3 $SKILL_PATH/scripts/signal_cron.py $STRATEGY_ID >> $SKILL_PATH/state/$TELEGRAM_USER_ID.$STRATEGY_ID.log 2>&1") | crontab -
  • high Dangerous commands cmd-persistence SKILL.md:101
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null; echo "0 9 * * * USER_ID=$TELEGRAM_USER_ID python3 $SKILL_PATH/scripts/review_cron.py $STRATEGY_ID >> $SKILL_PATH/state/$TELEGRAM_USER_ID.review.log 2>&1") | crontab -
Medium and low: 4
  • low Secrets in code secret-high-entropy-token credentials/example.json:2
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    "private_key": "0xYO…KEY",
    placeholder
  • low Risky intent intent-wallet-secrets scripts/polymarket.py:819
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target (quoted — discussed, not commanded)
    print("\nYou need your Polymarket wallet private key.")
    quoted
  • low Dangerous commands cmd-cron-mention SKILL.md:98
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null; echo "*/15 * * * * USER_ID=$TELEGRAM_USER_ID python3 $SKILL_PATH/scripts/signal_cron.py $STRATEGY_ID >> $SKILL_PATH/state/$TELEGRAM_USER_ID.$STRATEGY_ID.log 2>&1") | crontab -
  • low Dangerous commands cmd-cron-mention SKILL.md:101
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null; echo "0 9 * * * USER_ID=$TELEGRAM_USER_ID python3 $SKILL_PATH/scripts/review_cron.py $STRATEGY_ID >> $SKILL_PATH/state/$TELEGRAM_USER_ID.review.log 2>&1") | crontab -

Files scanned: 10. 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 53/100

  • 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. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 7 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1295 tokens

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)
  • +3Output format is not stated: the model decides each time
  • -31 of 7 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 147: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 7 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
This is a disclosed Polymarket trading bot, but it stores wallet secrets locally and can run persistent automated real-money trades with weak runtime safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026