sustainability-score is an open-source command-line tool that reads a code repository and flags engineering patterns that may affect energy, cloud-resource, and carbon efficiency. Its score is a directional triage signal built from repository files. It is not a measurement of runtime energy, and it is not a Software Carbon Intensity (SCI) score. Read the result as a list of places to investigate, not as a carbon footprint.
The question behind the tool is a fair one: are a codebase’s engineering choices pushing carbon up or down? A static scan can help you ask that question sharper. It cannot answer it alone.
As an Amazon Associate I earn from qualifying purchases.
What the scanner checks
The project, described by its author Sodek Timileyin in 2026, organizes its checks into five pillars. Each pillar carries a fixed weight in the overall score:
Recommended Free Tools
| Pillar | Weight |
|---|---|
| Code / Algorithm Efficiency | 30% |
| Cloud Infrastructure Choices | 25% |
| Containerization | 15% |
| CI/CD Practices | 15% |
| SRE / Operations | 15% |
The weights are the author’s design choices. They describe how the tool combines its pillars; they are not measured shares of real-world emissions.
#1 Best Overall
- Share your carbon footprint value on Twitter
- Find out what impact your commute has on your carbon footprint
- Become aware so you can make adjustments to your lifestyle
How the score is calculated
Each pillar starts at 100 points. Every finding then subtracts points according to its severity:
- High: minus 20 points
- Medium: minus 10 points
- Low: minus 4 points
As an illustration of the arithmetic, a pillar with one High finding and two Medium findings would score 100 − 20 − 10 − 10 = 60. The deduction values are reported design details from the author. The sources checked for this article include no published validation study showing that these deductions track actual energy use or emissions, and none that converts a score into emissions saved.
Data-quality tiers: how far a finding can claim to go
According to the author, every finding receives a data-quality tier. The tiers describe what evidence sits behind a claim:
| Tier | Evidence behind the finding | Claim the author permits |
|---|---|---|
| Tier 1 | Static analysis only | Directional |
| Tier 2 | Adds declared infrastructure | Not stated by the author |
| Tier 3 | Adds operational telemetry | Not stated by the author |
| Tier 4 | Direct measurement | Full SCI computable |
The author states that a static scan never claims above Tier 1. In the author’s words: “A static scan never claims above Tier 1. The report says plainly it is directional, not a measurement.” That limit is the most important thing to keep in mind when reading any report from this tool.
What an SCI score requires
The Green Software Foundation’s Software Carbon Intensity specification defines SCI as a rate: the total carbon caused by a software system, divided by a chosen functional unit. The total combines operational emissions, which come from energy use and the carbon intensity of the region where the software runs, with embodied emissions, which allocate hardware manufacturing emissions to the software’s use.
The specification’s reporting procedure has five steps:
- Define the software boundary.
- Choose a functional unit that reflects how the application scales, such as a request or a user action.
- Choose a quantification method for each component, using real-world telemetry or a model.
- Quantify each component.
- Report the score together with its boundary and methodology.
The specification accepts both measurements and models, and it encourages granular real-world data where it is available.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Why a repository scan cannot produce an SCI score
A scan reads source files, manifests, and pipeline definitions. Several inputs an SCI calculation needs are not in those files:
- Energy consumed per request or per functional unit, which depends on runtime behavior.
- The carbon intensity of the grid where the software actually runs.
- Embodied emissions for the hardware allocated to the workload.
- A defined whole-system boundary that includes everything the software depends on.
This limit follows from the tool’s own tiers and from the SCI specification’s measurement requirements. It is an inference, not a claim the author makes about every possible static tool.
Where code changes fit
The specification places software sustainability actions into three groups: energy efficiency, hardware efficiency, and carbon awareness. Its examples span code efficiency, model and database optimization, carbon-aware build scheduling, and infrastructure choices. Its discussion of software practitioners makes the link to code plain: “For a software programmer, this implies writing energy efficient code.”
That makes a useful comparison framework for any tool in this space. Ask whether it addresses source patterns, deployment and infrastructure, runtime measurement, or none of these, and whether it states its assumptions. Rank tools by that breakdown, not by which number looks bigger.
Windows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOutdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchRunning the scanner
- Clone the repository you want to check, then install the project from its root with
pip install -e . - Run the scan against your code with
sustainability-score /path/to/repo --md report.md, replacing the path with your repository’s location. - Open
report.mdand read the pillar scores and findings. Check each finding’s tier before deciding how much weight to give it. - Compare your output with the sample report included in the project to confirm you are reading the layout correctly.
- Check the project’s README for current options before scripting the command, since the instructions may change.
The project is described as MIT licensed and open source.
Limits and planned features
The project is described as a v0.1-style release. The author lists planned work: broader language checks, a JSON schema, a GitHub Action, and a proposal to the Green Software Foundation. These are stated plans, not confirmed features. Verify current behavior in the repository before relying on any of them.
No independently reported validation benchmark, measured emissions result, or correlation between this score and runtime carbon was found in the sources checked for this article. Treat the score as a prompt for investigation, and treat any claim about carbon reduction as something that needs its own measurement.
Pairing a scan with measurement
The scanner needs no special hardware. It runs on a repository checkout. Measurement is a separate step. A practical sequence is to use the scan to shortlist patterns worth examining, measure the paths that matter with runtime telemetry or direct measurement where you can, and document any model you use so others can check it. Measurement tools and code-level efficiency analyzers are complementary categories, and a repository review usually benefits from both.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
