SKILLEMALL.ai

BC Real Estate Investing

Analyze real estate investments with conservative underwriting, financing stress tests, diligence gates, and exit planning.

ClawHub Agent Skills author: Iván v1.0.0 MIT-0 11 files body ≈ 2 221 tokens Open the sourceclawhub.ai↗ analyzed 12 d ago

Analyze real estate investments with conservative underwriting, financing stress tests, diligence gates, and exit planning.

As a process C 56/100 · Has gaps — weak spots: result and completion, consistency, running it twice

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
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: 11. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "slug"
    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "changelog"

    Process rating: all ten parameters 56/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (Real Estate Investing) differs from the folder (real-estate-investing)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 58 steps, 1 vague phrases
    • 100Execution cost. Instruction body is 2221 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 13 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
    • +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
    • +3Description length 123: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 58 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

    External checks

    ClawHub: clean
    This is a coherent real-estate investing guidance skill that stores limited local notes and does not show hidden network, credential, privilege, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 12 Sept 2026