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 jamditis/claude-skills-journalism --skill photo-metadatagit clone --depth 1 https://github.com/jamditis/claude-skills-journalismWrote 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/jamditis/claude-skills-journalism/photo-metadata)<a href="https://agentmods.dev/skills/jamditis/claude-skills-journalism/photo-metadata"><img src="https://agentmods.dev/badge/skills/jamditis/claude-skills-journalism/photo-metadata/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/jamditis/claude-skills-journalism/photo-metadata"><img src="https://agentmods.dev/badge/skills/jamditis/claude-skills-journalism/photo-metadata.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.04133 |
| Opus 5 | $0.00019 | $0.02067 |
| Sonnet 5 | $0.00008 | $0.00827 |
| Haiku 4.5 | $0.00004 | $0.00413 |
Grade A, and why
photo-metadata 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 12d 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Photo metadata
Overview
Metadata embedded in an image file travels with the file. Photo CMSs (Photo Mechanic, Lightroom, Capture One) and wire intake systems read a photo's caption, credit, and rights from its IPTC and XMP blocks, not from a separate document or the email it arrived in. If the caption, credit, alt text, and license are not inside the file, they are gone the moment the photo is downloaded, forwarded, or re-uploaded.
One exiftool pass writes the EXIF, IPTC, and XMP layers together and leaves every other tag (camera settings, shot time) untouched. Modern software reads XMP first, legacy IPTC-IIM second, EXIF only for date and GPS, so write XMP everywhere and add IIM as a compatibility copy on JPEG/TIFF (HEIC, AVIF, and WebP have no IIM slot at all; see reference.md).
Two things changed since this workflow was "caption, credit, copyright." First, how an image was made now belongs in the metadata: the IPTC Digital Source Type field labels a camera photo versus an AI-generated one, and platforms (Meta, Google) and the EU AI Act increasingly read it. Second, cryptographic provenance (C2PA / "Content Credentials") is arriving on wire images and cameras, a signed layer exiftool can read but not write. Both are covered below.
A capable model already knows the field names. The hard part is not the mechanics, it is the judgment below. Lead with that.
When to use
- Prepping press photos for a wire so partner newsrooms can search, credit, and republish them
- Adding required photographer attribution and a reuse license before publishing or sharing
- Labeling how an image was made, a straight photo, an AI-generated illustration, an AI-edited composite
- Batch-tagging a shoot (a folder of images)
- Making images accessible (embedded alt text) and rights-clear (copyright or Creative Commons)
- Reading and sanity-checking the C2PA Content Credentials on an image that arrived from an agency
When not to use: editing pixels (this is metadata only); writing alt text for an HTML <img> (use accessibility-compliance); preserving web pages as evidence (use web-archiving); signing a Content Credential (exiftool can't, use c2patool, below).
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 182 lines · 38 tokens per session scan A 50a2b4f26148
photo-metadata is a skill published in the GitHub repository jamditis/claude-skills-journalism (391 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 4,133 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
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