SKILLEMALL.ai

AC horizontal-vertical-analysis

Deep-research skill for Chinese outputs using 横纵分析 / Horizontal-Vertical Analysis. Use when Codex needs to systematically study a product, company, concept, technology, market, or person: rebuild the full life-cycle on a vertical timeline, compare current peers or substitutes on a horizontal slice, cross the two axes into original insight, separate facts from inferences, and deliver a structured report or optional PDF. Not for quick definitions, gossip, or unsupported legal / investment due diligence.

ClawHub Agent Skills author: cellinlab v0.1.0 MIT-0 10 files body ≈ 757 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency

AnalyzerSoftware developmentData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
61/100
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: 10. 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: Deep-research skill for Chinese outputs using 横纵分析 / Horizontal-Ve… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 61/100

    • 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
    • 40Consistency. Frontmatter name (horizontal-vertical-analysis) differs from the folder (cell-horizontal-vertical-analysis)
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 81 steps
    • 100Execution cost. Instruction body is 757 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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 506: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 81 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is a coherent research-report skill with an optional local Markdown-to-PDF helper and no evidence of hidden data access, persistence, or exfiltration.
    LLM: benign (high) · VirusTotal: · 29 May 2026