SKILLEMALL.ai

AC leetcode-mock-interviewer

Conduct realistic LeetCode-style mock coding interviews. Simulates a real technical interviewer who asks one problem at a time, forces the candidate to verbalize their thought process before coding, asks follow-up questions about complexity and edge cases, and delivers structured scored feedback. Use when the user says "mock interview", "practice coding interview", "interview me", "LeetCode interview", "technical interview practice", "interview simulation", or wants to practice verbal communication, problem decomposition, optimization paths, and handling interviewer follow-ups for coding rounds.

ClawHub Agent Skills author: HJiang v1.0.0 MIT-0 6 files body ≈ 1 658 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
C
64/100
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

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: 6. 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 64/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 5 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 33 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1658 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 602: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 33 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    This is a markdown-only coding interview practice skill with no hidden access, execution, persistence, or credential use.
    LLM: benign (high) · 28 May 2026