SKILLEMALL.ai

AC interview-experience-rednotes

Collect, screen, download, OCR, and archive public Xiaohongshu (RedNote) interview-experience posts for non-technical roles, then optionally generate evidence-linked personalized answers from the user's resume and interview-preparation materials. Use when a candidate provides a JD alone or a JD plus personal materials for product, operations, sales, business development, design, marketing, functional, or management-trainee interviews. Produce matching Markdown, Word, and local HTML summaries and, when personal materials are available, matching answer documents. Do not use for coding interviews, mock interviews, resume rewriting, posting, messaging, or other social actions.

ClawHub Agent Skills author: Yang Rongkun v0.1.0 MIT-0 25 files · 3 scripts body ≈ 2 610 tokens Open the sourceclawhub.ai analyzed 2 d ago

Collect, screen, download, OCR, and archive public Xiaohongshu (RedNote) interview-experience posts for non-technical roles, then optionally generate…

As a process C 63/100 · Has gaps — weak spots: result and completion, running it twice

ProcedureWordWriting and documentsData and analyticsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
When it triggers w 12
50
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: 24. 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 63/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 7 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 50 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2610 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 top-level sections: this looks like several domains in one skill

    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
    • -31 of 6 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 681: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 50 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (6 of 6)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This skill is a disclosed Windows-focused research helper that collects public RedNote interview posts and creates local interview-prep documents, with substantial but purpose-aligned setup requirements.
    LLM: benign (high) · VirusTotal: · 6 Aug 2026