BF mena-property-listing-generator
AI-powered bilingual property listing generator for MENA real estate agents. Input: basic property specs. Output: SEO-optimized Arabic + English listing text, Instagram caption, TikTok script, Facebook post, and WhatsApp follow-up scripts. Use when user says 'create property listing', 'real estate listing', 'listing in Arabic', 'PropertyFinder listing', or wants to reduce manual copywriting time.
AI-powered bilingual property listing generator for MENA real estate agents.
As a process F 51/100 · Will not run — References files that are not bundled: references/arabic-copywriting.md, references/platform-formats.md, references/whatsapp-scripts.md
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- The text references files that are not there: add them or drop the references.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Exfiltration
net-redirectable-api-keyscripts/property_listing.py:246Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Missing closing "quote at line 14, column 32: the minimax LLM API endpoint. ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
missing-refreference to a missing file: references/arabic-copywriting.md - warning
missing-refreference to a missing file: references/platform-formats.md - warning
missing-refreference to a missing file: references/whatsapp-scripts.md - warning
missing-refreference to a missing file: references/brochure-templates.md - note
frontmatter-keyunknown frontmatter key "permissions" - note
frontmatter-keyunknown frontmatter key "privacy"
Process rating: all ten parameters 51/100
- 0Tools and files. 4 referenced file(s) missing: references/arabic-copywriting.md, references/platform-formats.md, references/whatsapp-scripts.md
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 49 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1156 tokens
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -42 reference files, but SKILL.md never points to them: the model will not open them
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 399: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 49 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.