SKILLEMALL.ai

AC ask-human-expert

Ask real human experts a question through Instant Expert and get a written or voice answer or a short call. It finds executives, operators and domain specialists by description, or reaches one named person by name and company, LinkedIn URL or email, and sends each a paid ask. The buyer pays only if the person answers or books, and approves every live order first. Use when the agent or user needs first-hand knowledge that search can't give (how practitioners actually do something, an expert opinion, customer discovery or user interviews, feedback from a specific kind of professional), wants to reach a specific person, or wants to check replies to earlier asks. Starts in a free test mode with no account or card.

ClawHub Agent Skills author: Max Kolysh v1.0.1 MIT-0 4 files · 1 script body ≈ 2 995 tokens Open the sourceclawhub.ai↗ analyzed 13 d ago

Ask real human experts a question through Instant Expert and get a written or voice answer or a short call.

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
99
Quality 40%
96
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Dangerous commands cmd-privilege scripts/ie.sh:105
      Privilege escalation / world-writable permissions (detector / deny-list definition; code comment)
      # scanners from reading the numeric mode as a setuid or root request.
      detectorcomment

    Files scanned: 4. 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 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 19 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 100Steps. 39 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2995 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 719: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 39 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: clean
    This skill is a disclosed Instant Expert integration for asking paid human experts, with clear test-mode separation and live-payment approval requirements.
    LLM: benign (high) · VirusTotal: · 10 Oct 2026