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 mizzlelover/portrait-prompt-atlas --skill gpt-image-2-portrait-librarygit clone --depth 1 https://github.com/mizzlelover/portrait-prompt-atlasWrote 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/mizzlelover/portrait-prompt-atlas/gpt-image-2-portrait-library)<a href="https://agentmods.dev/skills/mizzlelover/portrait-prompt-atlas/gpt-image-2-portrait-library"><img src="https://agentmods.dev/badge/skills/mizzlelover/portrait-prompt-atlas/gpt-image-2-portrait-library/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/mizzlelover/portrait-prompt-atlas/gpt-image-2-portrait-library"><img src="https://agentmods.dev/badge/skills/mizzlelover/portrait-prompt-atlas/gpt-image-2-portrait-library.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 | $0.00066 | $0.00944 |
| Opus 5 | $0.00033 | $0.00472 |
| Sonnet 5 | $0.00013 | $0.00189 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
gpt-image-2-portrait-library 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GPT Image 2 Portrait Library
Use this Skill to turn a real portrait-editing request into a source-aware recommendation. It is designed for client work, preservation work, and public research: the prompt, source link, publisher, authorship status, curation category, and website catalog are generated from one corpus.
Source of truth
- Read
references/portrait-library.mdfirst for the two-level portrait taxonomy and selection rules. - Use
references/portrait-records.jsonas the installed, complete source of truth. It includes all 519 curated original-language prompts and their hashes, source URLs, publisher/creator fields, identity controls, framing, and risk flags. - Use
node bin/portrait-prompt-atlas.mjs search --query "..."to narrow candidates. Useshow <record-id>to inspect a full record. Do not rely on memory for case IDs or attribution.
Modes
1. Find a collected prompt
- Identify both the primary task family and the secondary scenario. For example, use
professional_headshot_and_brand+business_headshot_and_profilefor a corporate avatar, butprofessional_headshot_and_brand+personal_branding_half_and_full_portraitfor a half/full-body personal-brand image. - Never select natural retouching for an illustration, sketch, anime, painting, or other non-photographic rendering; use
identity_locked_style_transferand its relevant secondary scenario instead. - Prefer
identity_lock: explicitwhen the request involves an existing person, a sentimental image, a family photo, or a client portrait. - Filter records by the task family, identity control, framing, and any needed terms. Read the complete candidate prompt before presenting it.
- Return one strongest match, or two to three clearly different matches if the request is ambiguous.
2. Adapt a collected prompt
Keep the collected prompt verbatim first. Then, only when asked, provide a separate Adaptation patch that lists exactly which variables or clauses change. Do not silently rewrite the record or call the adapted text the source prompt.
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 · 80 lines · 66 tokens per session scan A 4b3603467cf4
gpt-image-2-portrait-library is a skill published in the GitHub repository mizzlelover/portrait-prompt-atlas (7 stars, last pushed 3d ago), licensed MIT. It adds 66 tokens to every session and 944 once invoked, about $0.0003 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 2026-08-31.
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