SKILLEMALL.ai

AC task-boundary-auditor

Use when a user asks the AI to perform tasks that may exceed LLM capabilities, such as counterfactual reasoning, formal verification, real-time control, physical design, ethical judgment, zero-omission auditing, or extreme prediction. Also use when tasks mix safe and unsafe sub-tasks. Triggers: "verify all", "prove", "predict", "design a bridge/system", "what if X never happened", "ensure no omissions", "real-time monitor", "legal/medical judgment".

ClawHub Agent Skills author: tianzhiceng297-boop v1.0.0 MIT-0 2 files body ≈ 2 204 tokens Open the sourceclawhub.ai analyzed 2 d ago

Use when a user asks the AI to perform tasks that may exceed LLM capabilities, such as counterfactual reasoning, formal verification, real-time control…

As a process C 59/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

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 · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Use when a user asks the AI to perform tasks that may exceed LLM c… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 59/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2204 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 7 example trigger phrases
    • +3Description length 453: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 15 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: clean
    This skill is a markdown-only guidance skill that helps an agent recognize tasks beyond LLM capability and route them to humans or tools.
    LLM: benign (high) · VirusTotal: · 5 Jun 2026