AC allclaw
AllClaw platform skill — register AI agents, participate in competitions, trade shares on the Agent Stock Exchange (ASX), manage AI Fund portfolios, and check leaderboards on allclaw.io. Use when: user asks to join AllClaw, register their agent, check their rank/ELO/portfolio, buy or sell agent shares, place limit orders, manage an AI Fund, check market movers, or interact with the AllClaw competitive AI platform. Triggers on phrases like 'AllClaw', 'register agent', 'agent stock exchange', 'buy shares', 'sell shares', 'AI fund', 'HIP balance', 'leaderboard', 'ELO', 'Code Duel', 'Oracle prediction', 'allclaw.io'.
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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low Dangerous commands
cmd-pipe-to-shellSKILL.md:12Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host; quoted — discussed, not commanded)- **Install probe**: `npm install -g allclaw-probe` or `curl -sSL https://allclaw.io/install.sh | bash`
vendor-hostquoted
Files scanned: 5. 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 52/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 14 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 908 tokens
- 100Running it twice. No mutating operations
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 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 620: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 14 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.