SKILLEMALL.ai

AB real-estate-listing-coach

Coach real-estate agents and FSBO sellers through listing optimization — pricing strategy, MLS description writing, photo direction, staging priorities, marketing channel mix, open-house playbook, and negotiation prep. Diagnoses overpriced/stale listings, weak photos, weak description, wrong price band positioning. Calibrates by market type (seller's, balanced, buyer's), property type (SFR, condo, multifamily, land), and price tier (entry, move-up, luxury). Also coaches buyer's agents on offer strategy and listing critiques. Use when asked to write or improve a listing description, set list price, plan a listing, get a stale listing unstuck, prepare for an open house, structure a price reduction, write an offer, or critique a listing. Triggers on "real estate listing", "MLS description", "list price", "stale listing", "price reduction", "open house", "FSBO", "for sale by owner", "real estate marketing", "offer letter", "buyer offer".

ClawHub Agent Skills author: charlie-morrison v1.0.0 MIT-0 2 files body ≈ 3 098 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerAI and agentsInfrastructureSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
72/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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: 2. 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 72/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 100 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3098 tokens
    • low 11 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 947: 120–800 characters recommended
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 10 example trigger phrases
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 100 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This markdown-only real estate coaching skill is purpose-aligned and non-executable, with a privacy caveat around open-house contact collection.
    LLM: benign (high) · VirusTotal: · 29 May 2026