Turn confusing mattress marketing into practical, body-specific guidance on firmness, materials, durability, comparisons, and warranty coverage.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install mattress-spec-decoder
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install mattress-spec-decoder using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Mattress Spec Decoder?
Mattress Spec Decoder is an offline Python skill that helps shoppers evaluate mattresses using the specifications that influence performance: foam density, ILD, coil type and count, and layer order. Instead of relying on brand names or claims such as “cooling gel,” it translates product details into durability assessments, expected lifespan, and a firmness recommendation based on sleep position and BMI.
As one of the practical Openclaw Skills for informed mattress shopping, it can compare two beds for an individual or help couples reason through different sleep profiles. It also explains warranty thresholds and prorated coverage, while keeping the focus on consumer guidance—not medical diagnosis.
Mattress Spec Decoder Use Cases
- You are shopping online or in a store and need to compare mattresses by their actual materials rather than model names.
- A spec sheet lists foam densities, coil details, or ILD values and you want to understand what they imply for durability and feel.
- You need a firmness starting point based on sleep position, weight, and height.
- You are choosing between foam, latex, hybrid, or innerspring construction.
- Two sleepers have different body profiles and need a practical firmness compromise.
- You want to assess whether a warranty’s sag threshold or prorated terms offer meaningful coverage.
- Your mattress is sagging and you want to compare the measured dip with the stated warranty threshold.
- You are evaluating a mattress you already own and considering whether a topper could help.
How Mattress Spec Decoder Works
- Build a sleeper profile. Run
recommendwith sleep position, weight, and height to get a firmness band, target ILD, possible mattress types, and relevant body-specific cautions. - Decode construction details. Run
decodewith the mattress type and available layer, density, and coil specifications to assess durability and identify less meaningful marketing claims. - Compare candidate beds. Run
comparewith a sleeper profile and two mattress descriptions to receive a weighted assessment across support fit, durability, motion isolation, heat, and edge support, with reasoning for each criterion. - Check warranty terms. Use
warrantyto examine the sag threshold, prorated schedule, and coverage conditions; usesagto assess a measured dip against a threshold and ownership period. - Verify before buying. Confirm specifications with the manufacturer, review the trial period, and use the buying playbook for model fingerprinting, floor-model math, and delivery inspection.
Mattress Spec Decoder Setup
The skill uses Python 3’s standard library, works offline, and requires no package installation. Run the script from the skill directory. Example commands:
# Get a firmness recommendation
python3 scripts/mattress_advisor.py recommend --position side --weight 78 --height 175
# Decode a hybrid mattress spec sheet
python3 scripts/mattress_advisor.py decode --type hybrid \
--memory-density 3.0 --base-density 1.5 --coils 480 --coil-type pocketed
# Check a prorated warranty with a 1.5-inch sag threshold
python3 scripts/mattress_advisor.py warranty --years 10 --prorated --sag-threshold 1.5
For a couple, use couple with both sleeper profiles. To compare two beds, use compare with a profile and mattress specifications; to assess an existing dip, use sag with its measured depth, threshold, and years owned. The skill does not require a network connection or third-party Python dependencies.
Mattress Spec Decoder Data Schema & Taxonomy
The skill takes command-line arguments and mattress specifications; the supplied documentation does not describe a database, persistent user profile, or generated data files.
| Data area | Example fields | Purpose |
|---|---|---|
| Sleeper profile | Position, weight, height | Estimate a suitable firmness band and body-specific considerations |
| Mattress construction | Type, memory-foam density, base-foam density, coil count, coil type | Assess materials, support construction, and durability |
| Comparison profile | Sleeper profile plus two named mattress specifications and prices | Score the options across fit, durability, motion isolation, heat, and edge support |
| Warranty and sag | Warranty years, prorated status, sag threshold, measured dip, years owned | Interpret coverage terms and assess a sag measurement |
The skill includes scripts/mattress_advisor.py for its command-line workflows and references for deeper guidance: references/mattress-science.md covers materials and construction, while references/buying-playbook.md covers shopping and inspection tactics. Mattress specifications are supplied to the relevant command rather than organized into a documented persistent catalog.
Mattress Spec Decoder Advanced Features
- Couple recommendations: Evaluate two sleepers with different positions and body profiles; the documented approach uses the higher firmness need and addresses pressure relief with a comfort layer, with split-core or dual-firmness options when the gap is large.
- Profile-aware firmness logic: Starts with position-based firmness and adjusts for BMI; BMI of 30 or higher adds a high-density support requirement.
- Criterion-level comparisons: Score two mattresses for a specific sleeper across support fit, durability, motion isolation, heat, and edge support, with reasoning rather than a bare ranking.
- Warranty analysis: Examine prorated coverage and sag thresholds, including a separate measured-sag assessment.
- Material and lifespan guidance: Evaluate foam density, latex density, coil count and gauge, and layer construction using the skill’s reference material.
- Offline, dependency-light operation: Runs with Python 3’s standard library and makes no network connection.
- Shopping playbook: Provides guidance on identifying equivalent mattresses across retailer-specific model names, evaluating floor models, inspecting delivery, and considering a topper for an existing mattress.
SKILL.md
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