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Agent skill

Sdr Mosaic Data

by isetbio in isetbio/isetbio

Create, publish, organize, or fetch the ISETBio retinal mosaic data deposit in the Stanford Digital Repository (SDR).

MITAuto-check passed

Install Sdr Mosaic Data

skills CLI
$ npx skills add isetbio/isetbio --skill sdr-mosaic-data -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install isetbio/isetbio sdr-mosaic-data --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/isetbio/isetbio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/sdr-mosaic-data .claude/skills/sdr-mosaic-data && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
sdr-mosaic-data
GitHub stars
115
Token cost
~1.6k tokens
SKILL.md length
771 words
Files
4 (incl. references)
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Create, publish, organize, or fetch the ISETBio retinal mosaic data deposit in the Stanford Digital Repository (SDR).

  • Works in 4 steps: Inspect the staged root and every… → Create the SDR collection/deposit named… → The first public release is PURL… → …
  • SDR collection/deposit setup
  • SKILL.md covers Published deposit, Deposit workflow, Fetch and cache design and API and test boundaries, plus 2 more sections
  • Calls git; reaches purl.stanford.edu and stacks.stanford.edu

What it does

Sdr Mosaic Data is an agent skill from isetbio/isetbio. Create, publish, organize, or fetch the ISETBio retinal mosaic data deposit in the Stanford Digital Repository (SDR). Use for SDR collection/deposit setup, PURL or Stacks download-root capture, staged manifests, ISETCam ieWebGet registry and download support, or the ISETBio manifest-aware untracked mosaic-data cache.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `agents/openai.yaml`, `references/current-state.md` and `references/iewebget-and-cache.md`).

The repository describes itself as: Tools for modeling image systems engineering in the human visual system front end. The licence is MIT.

When your agent uses it

  • SDR collection/deposit setup
  • Stacks download-root capture
  • Staged manifests
  • ISETCam ieWebGet registry and download support

Example prompts

  • “/sdr-mosaic-data”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Inspect the staged root and every manifest before uploading. Preserve the
  2. Create the SDR collection/deposit named isetbio-mosaics, retaining the
  3. The first public release is PURL https://purl.stanford.edu/vm447vf0975,
  4. Compare uploaded file sizes/checksums with the staged manifests before

What it can do on your machine

Read from SKILL.md and the folder at commit d2924c2. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • purl.stanford.edu
    • stacks.stanford.edu

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sdr Mosaic Data loads about 1.6k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 771 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from isetbio/isetbio at commit d2924c2, republished under its MIT licence (© isetbio). 771 words, ~1,586 tokens.

Download SKILL.mdSave it as .claude/skills/sdr-mosaic-data/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
sdr-mosaic-data
description
Create, publish, organize, or fetch the ISETBio retinal mosaic data deposit in the Stanford Digital Repository (SDR). Use for SDR collection/deposit setup, PURL or Stacks download-root capture, staged manifests, ISETCam ieWebGet registry and download support, or the ISETBio manifest-aware untracked mosaic-data cache.

SDR Mosaic Data

Use this skill for the ISETBio isetbio-mosaics SDR workflow. Read references/current-state.md first. Then read local/MOSAIC-LOAD.md when it is available; it is the detailed design record and remains authoritative for the loader contract and deferred decisions.

Published deposit

isetbio-mosaics is published at https://purl.stanford.edu/vm447vf0975 (DRUID vm447vf0975). Its verified Digital Stacks download root is https://stacks.stanford.edu/file/vm447vf0975. Both manifest.json and a nested mosaic asset have been verified at that root. Keep the deposited directory hierarchy intact when resolving relative manifest paths.

Deposit workflow

  1. Inspect the staged root and every manifest before uploading. Preserve the four collection directories and their nested left/right paths. Do not include data_sabesan unless its separate collection and metadata contract have been approved.
  2. Create the SDR collection/deposit named isetbio-mosaics, retaining the hierarchy. Use the top-level README.md for the plain-language file guide and the SDR description for the short catalog-level summary.
  3. The first public release is PURL https://purl.stanford.edu/vm447vf0975, DRUID vm447vf0975, with Stacks root https://stacks.stanford.edu/file/vm447vf0975. For later versions, record the public version and re-test manifest.json plus one nested MAT-file URL. Do not derive a download root from a guessed URL pattern.
  4. Compare uploaded file sizes/checksums with the staged manifests before treating the deposit as ready for loader work.

Fetch and cache design

Use ISETCam's ieWebGet; do not add a second HTTP downloader in ISETBio. The current implementation is ../isetcam/utility/file/ieWebGet.m. Its SDR registry is private (urlDeposit) and its cases are resource-specific, so adding a registry row alone is not enough for arbitrary manifest paths.

  • The isetbio-mosaics ISETCam resource records the PURL for browsing and the verified Stacks root for files. ieWebGet accepts one SDR-relative asset path plus a caller-supplied destination, and deposit file = 'all' mirrors every manifest-listed asset.
  • Set the default ISETBio cache root to fullfile(isetbioRootPath, 'data', 'sdr'). data/sdr/.gitignore excludes downloaded files from Git. The resulting cache must be <cache-root>/isetbio-mosaics/<collection>/<eye>/<file>.mat.
  • mosaicLoad fetches manifest.json before resolving a cone mosaic, looks up an exact record, and does not reconstruct a remote filename from MATLAB arguments. It downloads to a temporary sibling, verifies SHA-256 and byte count, then renames into the mirrored cache path. It verifies cache hits and replaces corrupt entries.

See references/iewebget-and-cache.md for the interface and validation details.

Show full SKILL.md (412 more words)Show less

API and test boundaries

Keep mosaicLoad, cone/mRGC lattice importers, and mRGCMosaic.loadPrebakedMosaic as public entry points. Place remote resolution below them. Do not repurpose cMosaic's name parameter, modify the staged file layout casually, or rewrite Git history.

All four collections are migrated. The shared fetch layer is in utility/sdr/: sdrMosaicCacheRoot, sdrMosaicRecords, sdrMosaicFetch, sdrMosaicVerify, sdrLegacyFilenameMap, and sdrPrebakedCircuitFile. Lattices resolve through retinalattice.import.sourceLatticeFile. A locally generated file always wins over the deposited copy, so the three gallery directories remain, each with a README. Add a new collection by resolving through these helpers rather than writing a second fetch path.

Circuits are selected by their historical ISETBio filename, not by manifest metadata. Staging dropped the sign of the x eccentricity for mrgc_on_circuits, so x = -2 and x = +2 both read [2 0]. The legacy map at data/datafiles/sdr/isetbio-mosaics-legacy-filenames.json is the lookup table; every pairing in it was established by SHA-256 comparison. Before deleting any bundled asset, confirm it is byte-identical to its deposited copy.

Keep core unit tests offline and deterministic. Live checks are named FullOnly: test_sdrMosaicCacheFullOnly covers first fetch, cache hit, corrupt-cache replacement, missing records, and golden crop parity; test_sdrLegacyFilenameMapFullOnly checks the map against the manifests and fails once the eccentricity sign is fixed. Offline fake-transport tests are still outstanding and need an injection seam, since sdrMosaicFetch calls ieWebGet directly and sdrMosaicCacheRoot is fixed.

Documentation follow-up

docs/sdr-mosaic-data.md is the user-facing account of the deposit: loading, the cache, full-deposit mirroring, locally generated data, and troubleshooting. docs/major-changes.md carries the compatibility entry. Update both when loader behavior changes.

The wiki (isetbio/wiki) is still to be written, and docs/sdr-mosaic-data.md is its intended source. The repository docs/ directory may later become a set of pointers to wiki pages; do not restructure it as part of loader work.

Deferred Git-history cleanup

Removing a migrated asset from the current tree is a normal commit and makes future repository checkouts smaller only when paired with a later history rewrite. Do not rewrite history yet. Revisit that separate project no earlier than August 2027 (the deposit was published 2026-08-10), once the SDR loader and deposit have proven stable and downstream users have migrated.

At that time, preserve the SDR PURL, manifests, checksums, and a verified bare repository backup before using a scoped git filter-repo rewrite to remove only approved migrated paths. Inventory release tags, branches, forks, and downstream repositories; announce the force-push/re-clone cutover; then verify a fresh clone, the affected releases, and representative SDR loads. Never rewrite history merely to reduce repository size without that coordination.

© isetbio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in .github/skills/sdr-mosaic-data of isetbio/isetbio.

  • SKILL.md
  • agents/openai.yaml
  • references/current-state.md
  • references/iewebget-and-cache.md

Open the folder on GitHubat commit d2924c2

Compare with similar skills

Sdr Mosaic Data next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Sdr Mosaic Data compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Sdr Mosaic Data this skillisetbio/isetbio115—~1.6kAutomated safety check: PassMIT
Publishcode-yeongyu/oh-my-openagent70k—~5.5kAutomated safety check: WarnCustom licence
Social Publisheraffaan-m/ECC276k1 repos~1.1kAutomated safety check: PassMIT
Publishyc-software/qm15k—~2.2kAutomated safety check: WarnMIT
Organizationthedaviddias/Front-End-Checklist74k—~609Automated safety check: PassMIT
Social Publishingwshobson/agents40k—~914Automated safety check: PassMIT

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More from isetbio/isetbio

All 9 skills in this repo

  • Matlab Environment

    isetbio/isetbio

    Configure or troubleshoot a local MATLAB and VS Code environment for ISETBio.

    115 GitHub stars~558 tokensUpdated 13 days ago
    Auto-check passed

  • Matlab Evaluation

    isetbio/isetbio

    Run MATLAB non-interactively from a shell on this machine — locating the MATLAB binary, setting ISETCam/ISETBio paths for a batch session, and invoking -batch evaluation.

    115 GitHub stars~568 tokensUpdated 13 days ago
    Auto-check passed

  • Matlab Testing

    isetbio/isetbio

    Develop, run, diagnose, or report ISETBio MATLAB tests. An agent skill from isetbio/isetbio.

    115 GitHub stars~884 tokensUpdated 13 days ago
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  • Retinal Mosaic Data

    isetbio/isetbio

    Work with ISETBio cone and midget-RGC mosaic data, including loading, generating, migrating, caching, or reviewing lattices, serialized cMosaics, pre-baked mRGCMosaics, and compute-ready mosaics.

    115 GitHub stars~1.5k tokensUpdated 13 days ago
    Auto-check passed

  • Tutorial Example Authoring

    isetbio/isetbio

    Create, move, review, publish, or test ISETBio tutorials, examples, and data-generation scripts.

    115 GitHub stars~560 tokensUpdated 13 days ago
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  • Matlab Script Review

    isetbio/isetbio

    Review existing ISETBio MATLAB tutorial, example, or demo scripts without implementing behavior.

    115 GitHub stars~655 tokensUpdated 13 days ago
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Questions about Sdr Mosaic Data

What does Sdr Mosaic Data do?

Create, publish, organize, or fetch the ISETBio retinal mosaic data deposit in the Stanford Digital Repository (SDR). Sdr Mosaic Data is an agent skill from isetbio/isetbio. Create, publish, organize, or fetch the ISETBio retinal mosaic data deposit in the Stanford Digital Repository (SDR).

When should I use Sdr Mosaic Data?

Sdr Mosaic Data fits situations like: SDR collection/deposit setup; stacks download-root capture; staged manifests; ISETCam ieWebGet registry and download support.

How do I install Sdr Mosaic Data in Claude Code?

Run `npx skills add isetbio/isetbio --skill sdr-mosaic-data -a claude-code`. Or copy the skill folder (.github/skills/sdr-mosaic-data in isetbio/isetbio) into .claude/skills/sdr-mosaic-data in your project. Claude Code loads it when a task matches its description.

How do I install Sdr Mosaic Data in Codex?

Run `npx skills add isetbio/isetbio --skill sdr-mosaic-data -a codex`. Or copy the skill folder (.github/skills/sdr-mosaic-data in isetbio/isetbio) into .agents/skills/sdr-mosaic-data in your project. Codex loads it when a task matches its description.

Can I use Sdr Mosaic Data in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add isetbio/isetbio --skill sdr-mosaic-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sdr-mosaic-data, .gemini/skills/sdr-mosaic-data, .github/skills/sdr-mosaic-data and .opencode/skills/sdr-mosaic-data in your project.

What does Sdr Mosaic Data need to run?

Going by SKILL.md and its folder, Sdr Mosaic Data needs the command-line tools its instructions call (git).

Does Sdr Mosaic Data access the network?

SKILL.md names 2 domains. In commands or code: purl.stanford.edu and stacks.stanford.edu; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Sdr Mosaic Data safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Sdr Mosaic Data use?

Sdr Mosaic Data is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sdr Mosaic Data use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Sdr Mosaic Data?

Skills that share tags, products or a category with Sdr Mosaic Data: Publish (code-yeongyu/oh-my-openagent, 70k stars), Social Publisher (affaan-m/ECC, 276k stars), Publish (yc-software/qm, 15k stars) and Organization (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sdr Mosaic Data?

isetbio (a GitHub organization) maintains it in isetbio/isetbio, which has 115 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 25, 2026.

Source: isetbio/isetbio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.