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microscopy-scale-bar-adder

Add accurate, publication-ready scale bars to microscopy images given pixel-to-unit calibration data.

Install / Use

npx skills add aipoch/medical-research-skills --skill microscopy-scale-bar-adder

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

88/100

Supported Platforms

Universal

Our assessment of microscopy-scale-bar-adder

microscopy-scale-bar-adder scores 88/100 on our quality scale, 413th of 960 Content & Media skills we index (top 44%).

Its SKILL.md is 6.2 KB long, well organised into 16 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

With 1,916 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
18/20
Description
12/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 13 days ago, so microscopy-scale-bar-adder is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

microscopy-scale-bar-adder compared with similar skills

All 4 of these similar skills score higher than microscopy-scale-bar-adder; compare them before choosing.

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microscopy-scale-bar-adder (this skill)by aipoch881.9k13d agoSKILL.md
Agent-Reachby Panniantong10086.4k15d agoCLAUDE.md
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Frequently asked questions

How do I install microscopy-scale-bar-adder?
Run npx skills add aipoch/medical-research-skills --skill microscopy-scale-bar-adder. The install tabs above show the steps for each supported agent.
Which AI agents does microscopy-scale-bar-adder work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is microscopy-scale-bar-adder safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is microscopy-scale-bar-adder still maintained?
The repository was last updated 13 days ago, so microscopy-scale-bar-adder is actively maintained.

name: microscopy-scale-bar-adder description: Add accurate, publication-ready scale bars to microscopy images given pixel-to-unit calibration data. license: MIT author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Microscopy Scale Bar Adder

Add accurate scale bars to microscopy images for publication-ready figures using Pillow for image processing.

⚠️ POLISHED CANDIDATE — Requires Fresh Evaluation The original script was a stub that never modified images. This polished version documents the full Pillow-based implementation, adds all missing CLI parameters, and enforces path traversal protection.

When to Use

  • Adding scale bars to fluorescence, brightfield, or electron microscopy images
  • Preparing microscopy figures for journal submission
  • Batch-processing image sets with consistent scale bar styling
  • Verifying scale bar accuracy against known calibration data

Workflow

  1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
  2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
  3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
  4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
  5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Usage

# Add a 50 µm scale bar to a TIFF image
python scripts/main.py --image image.tif --scale 50 --unit um

# Specify output path and bar position
python scripts/main.py --image image.tif --scale 10 --unit um --output annotated.tif --position bottomright

# Custom bar and label colors
python scripts/main.py --image image.tif --scale 100 --unit nm --bar-color white --label-color white --bar-thickness 4

Parameters

| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | --image | path | Yes | - | Input image file path | | --scale | float | Yes | - | Scale bar length in physical units | | --unit | str | No | um | Unit: um, nm, mm | | --pixels-per-unit | float | No | from TIFF metadata | Calibration override (pixels per unit) | | --output | path | No | <input>_scalebar.<ext> | Output file path | | --position | str | No | bottomright | Bar position: bottomright, bottomleft, topright, topleft | | --bar-color | str | No | white | Scale bar fill color | | --label-color | str | No | white | Label text color | | --bar-thickness | int | No | 3 | Bar height in pixels |

Implementation Notes (for script developer)

The script must implement using PIL.Image, PIL.ImageDraw, PIL.ImageFont:

  1. Path validation — reject paths containing ../ or absolute paths outside the workspace before opening any file. Print Error: Path traversal detected: {path} to stderr and exit with code 1.
  2. Image open — PIL.Image.open(args.image). Raise FileNotFoundError if missing.
  3. Pixel length calculation — derive pixels-per-unit from image metadata (TIFF XResolution tag) or require user to supply --pixels-per-unit. Scale bar pixel length = scale * pixels_per_unit.
  4. Draw scale bar — use PIL.ImageDraw.Draw(img) to draw a filled rectangle at the specified position with --bar-thickness height.
  5. Draw label — use PIL.ImageFont to render "{scale} {unit}" above or below the bar.
  6. Save output — img.save(output_path). Print the output path to stdout.

Features

  • Automatic scale bar pixel length calculation from calibration metadata or user-supplied --pixels-per-unit
  • Support for common microscopy formats: TIFF, PNG, JPG, BMP
  • Configurable bar size, color, and label style (--bar-color, --label-color, --bar-thickness)
  • Configurable position: bottomright, bottomleft, topright, topleft
  • Preserves original image resolution and metadata
  • Path traversal protection (rejects ../ paths and absolute paths outside workspace)

Quick Check

python -m py_compile scripts/main.py
python scripts/main.py --help

Input Validation

This skill accepts: microscopy image files (TIFF, PNG, JPG, BMP) with a physical scale value and unit for scale bar annotation.

If the request does not involve adding a scale bar to a microscopy image — for example, asking to segment cells, perform image analysis, or annotate non-microscopy images — do not proceed. Instead respond:

"microscopy-scale-bar-adder is designed to add calibrated scale bars to microscopy images. Your request appears to be outside this scope. Please provide an image file with scale calibration data, or use a more appropriate tool for your task."

Error Handling

  • If --image or --scale is missing, state exactly which fields are missing and request only those.
  • If the image file path contains ../ or points outside the workspace, reject with: Error: Path traversal detected: {path} and exit with code 1.
  • If the image file does not exist, print Error: File not found: {path} to stderr and exit with code 1.
  • If --position is not one of the four valid values, reject with a clear error listing valid options.
  • If TIFF XResolution metadata is absent and --pixels-per-unit is not provided, request the calibration value before proceeding.
  • If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
  • If scripts/main.py fails, report the failure point and summarize what can still be completed.
  • Do not fabricate scale values or calibration data.

Fallback Template

When execution fails or inputs are incomplete, respond with this structure:

FALLBACK REPORT
───────────────────────────────────────
Objective      : [restate the goal]
Blocked by     : [exact missing input or error]
Partial result : [what can be completed without the missing input]
Next step      : [minimum action needed to unblock]
───────────────────────────────────────

Response Template

  1. Objective
  2. Inputs Received
  3. Assumptions
  4. Workflow
  5. Deliverable
  6. Risks and Limits
  7. Next Checks

Prerequisites

Requires Pillow: pip install Pillow

Related Skills

View on GitHub
GitHub Stars1.9k
CategoryContent
Updated13d ago
Forks175

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions