SKILLEMALL.ai

AC hotel-revenue-pacing-report

Use this skill when a hotel revenue manager, director of revenue management, or general manager needs to draft a weekly or monthly revenue pacing analysis report. Covers occupancy, ADR, RevPAR, pacing vs. budget and prior year, segment performance, competitive set benchmarking, forward-demand review, and pricing strategy recommendations. Produces a DRAFT report for revenue manager review before distribution to ownership or leadership.

ClawHub Agent Skills author: devasher v0.1.0 MIT-0 4 files body ≈ 2 243 tokens Open the sourceclawhub.ai analyzed 2 d ago

Covers occupancy, ADR, RevPAR, pacing vs.

As a process C 63/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 4. 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 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 65Failures and branches. 3 branches
    • 85Steps. 48 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2243 tokens

    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)
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +3Description length 438: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 48 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    The skill set is mostly coherent for ClawHub maintainer work, but one review helper defaults to running a nested agent with unrestricted local access.
    LLM: suspicious (medium) · VirusTotal: · 2 Jun 2026