SKILLEMALL.ai

AB research-analysis

McKinsey-style business research and analysis skill. This skill should be used when the user needs consulting-grade insights, quantitative data modeling, competitor deep-dive analysis, user persona research, industry trend reports, or structured business problem-solving. Triggers on requests like analyze this market, compare competitors, build a user persona, estimate market size, write a research report, do a SWOT analysis, or any business research task requiring structured frameworks and data-driven conclusions.

ClawHub Agent Skills author: nannl22 v1.0.0 MIT-0 7 files body ≈ 1 788 tokens Open the sourceclawhub.ai analyzed 28 h ago

McKinsey-style business research and analysis skill.

As a process B 66/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

AnalyzerResearchData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Failures and branches w 10
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "permissions"
    • note frontmatter-key unknown frontmatter key "agent_created"

    Process rating: all ten parameters 66/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 46 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1788 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 519: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 46 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a coherent business research skill that openly guides web/company-data lookups and chart generation, with privacy caution needed for user-research outputs.
    LLM: benign (high) · VirusTotal: · 1 Aug 2026