Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vladolaru/claude-code-plugins --skill image-optimizationgit clone --depth 1 https://github.com/vladolaru/claude-code-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vladolaru/claude-code-plugins/image-optimization)<a href="https://agentmods.dev/skills/vladolaru/claude-code-plugins/image-optimization"><img src="https://agentmods.dev/badge/skills/vladolaru/claude-code-plugins/image-optimization/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vladolaru/claude-code-plugins/image-optimization"><img src="https://agentmods.dev/badge/skills/vladolaru/claude-code-plugins/image-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.04050 |
| Opus 5.5 | $0.00029 | $0.01620 |
| Sonnet 5.5 | $0.00014 | $0.00810 |
| Haiku 4.5 | $0.00007 | $0.00405 |
Grade A, and why
image-optimization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Optimization
Scripts do the mechanics (encoding, measuring, gating, crops, writing); you do the judgment (where an image is used, how big it is shown, which profile); the human gives the verdict on anything that changes pixels.
Rules
These hold over every step below.
- The human decides every pixel change. A variant that changes pixels is written only after the human kept that exact variant on the page (
applyenforces this; a copy you make does not), and a gate-failing variant becomes a choice only on their word. - View before you vouch. Open every tile
sheetmarks REQUIRED at its natural size before calling a choice good, and list the tiles you viewed. Viewing is not measuring: a reported-only metric (JPEG, WebP, AVIF banding) is never "passed". - The human installs tools. Quote what
doctorlists, with what each tool adds and its install line, and wait. - Every problem line reaches the human. Pass on each per-file line a command prints.
The tool
Every command is python3 "$SKILL_DIR/../../scripts/imgopt.py" <command>, written IMGOPT <command> below. Spell it out in each shell command, or define a function in that same command: imgopt() { python3 "$SKILL_DIR/../../scripts/imgopt.py" "$@"; }. Never run it from a shell variable ($IMGOPT): zsh does not word-split an unquoted variable, so the command is not found. Use plain python3, never python3 -I (Pillow may live in user site-packages). IMGOPT <command> --help lists every flag.
| Command | Use it to |
|---|---|
doctor --job <audit|recompress|prepare|convert|compare> --profile <p> [--format f] [paths] |
Check tools before any work (prepare = resizing, convert = a new format) |
inspect <paths> [--json] |
Report facts and lossless headroom; changes nothing (the audit job) |
workdir <task> |
A stable working folder for --out |
candidates <paths> [--files <list>] --out <dir> --profile <p> [--resize W] [--format f] [--ref file | --ref-rev REV] [--min-saving <bytes>] [--assume-srgb] [--jobs N] |
Try encoder settings per file, measure, gate, and set each file's default choice |
sheet <dir>... |
1:1 tiles for you, one review page for the human over every folder named |
variants <dir>... --file <f> |
Every measured variant of one file |
choose <dir>... --file <f> (--label L | --milder | --stronger | --default) |
Set one file's variant |
record [<dir>...] --verdicts - |
Store the verdict block the human pasted (in the folders the block names) |
apply <dir>... [--only a,b | --files list] [--dest dir] |
Write the accepted choices and re-measure them |
manifest <dir>... [--accepted] [--json] |
Each file's chosen variant path, its target and the metadata it removes |
compare <ref> <new> |
Measure any pair (path, git:<rev>:<path>, URL) and get the reviewer check |
clean <dir> [--keep-picks] |
Delete the working folder, or with --keep-picks only its unchosen variants |
clean --store [--older-than DAYS] |
Prune the shared variant store |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 113 lines · 72 tokens per session scan A f2d13470274b
image-optimization is a skill published in the GitHub repository vladolaru/claude-code-plugins (8 stars, last pushed 4d ago), licensed MIT. It adds 72 tokens to every session and 4,050 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-13.
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