Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/event4u-app/agent-confignpx agentmods add skills/event4u-app/agent-config/character-consistencyWrote 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/event4u-app/agent-config/character-consistency)<a href="https://agentmods.dev/skills/event4u-app/agent-config/character-consistency"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/character-consistency.svg" alt="Measured on agentmods" 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 | $0.00043 | $0.02118 |
| Opus 5 | $0.00022 | $0.01059 |
| Sonnet 5 | $0.00009 | $0.00424 |
| Haiku 4.5 | $0.00004 | $0.00212 |
Grade A, and why
character-consistency 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 8d 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
character-consistency
Lock a character's visual identity into
agents/reference/ai-video/<project>/characters/<id>.jsonso every scene reuses the exact same tokens verbatim. Downstream skills (video-director,pixar-storyteller,motion-choreographer) read this file and never paraphrase. Verified by visual regression (pixel similarity ≥ 95%, Phase 6 Step 3).
When to use
- A multi-scene run names the same character on screen more than once — Character Lock is mandatory before the second scene drafts.
- A character drift bug landed (face / outfit / prop changed between scenes) — re-lock and rerun the affected scenes.
- A series, episode, or recurring ad uses the same on-screen identity.
Do NOT use when:
- One-shot scene with no recurring character — overhead is wasted.
- The "character" is an environment or set (a place, not an
entity) — use a
style.jsonlock pattern in the project's notes instead. Recurring creatures, vehicles, and hero objects DO get a real lock — pick the matchingsubject_classbelow.
Procedure
Step 0: Inspect
- Check
agents/reference/ai-video/<project>/characters/— if a lock already exists for this id, read it, do not redraft. Edits require an explicit revision note (Phase 6 visual regression must rerun). - Confirm the character will appear in ≥ 2 scenes; one-shot → skip.
Step 1: Draft identity tokens
Emit a JSON file at
agents/reference/ai-video/<project>/characters/<character-id>.json with the
following fields. Every field is mandatory; missing field → fail
the lock.
{
"id": "kebab-case-id",
"name": "Display Name",
"subject_class": "humanoid | creature | vehicle | abstract | object",
"silhouette": "one-line read of the body shape from 30m",
"palette": ["#hex1", "#hex2", "#hex3"],
"wardrobe": "garment list, materials, era",
"signature_prop": "the one object that travels with them",
"posture_default": "how they stand when not acting",
"eye_behavior": "blink rhythm, glance habit",
"face": "age band, skin tone, hair (length / color / texture), distinguishing marks",
"voice_note": "timbre + cadence for native-audio adapters; null if N/A",
"reference_frame": "scenes/<id>/frames/<n>.png or null",
"version": 1
}
What ships with it
1 file 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.
- 8d ago First seen · 196 lines · 43 tokens per session scan A 8d8293f317ae
character-consistency is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 2,118 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 2026-08-31.
Other skills, from other repositories
starreel-drama-production
Operating skill for any AI agent driving the StarReel short-drama production pipeline (script → rewrite → extract → portraits + sheets → storyboards → frames → video → voiceover → final cut) over MCP or REST. Covers the ordered workflow, the entry-point decision table (which channel each kind of customer material…
seedance-20
Generate and direct cinematic AI videos with Seedance 2.0 (ByteDance/Dreamina/Jimeng). Covers text-to-video, image-to-video, video-to-video, and reference-to-video workflows with @Tag asset references, multi-character scenes, audio design, and post-processing. Use when making AI video, writing Seedance prompts…
seedance-2-5
Generate 4-30 second cinematic video with ByteDance Seedance 2.5 through fal.ai, Volcengine Ark, Runway, or ComfyUI Partner Nodes. Use for long single generations, synchronized audio, and large multimodal reference sets (up to 30 images, 10 videos, and 10 audio clips). Also covers the 2.5 prompt contract: section…
create-chatgpt-mockup
Render pixel-accurate ChatGPT mobile (iOS) screen mockups in light mode from a thread JSON. Supports user text bubbles, user image attachments, assistant markdown prose, citation chips, the OpenAI spiral logo, the Apps-SDK GPT chip in the composer, and three header styles (model-tag, plain title, "Get Plus"). Fixed…
comfyui
Use when working with ComfyUI workflows in OpenMontage, including comfyuiimage/comfyuivideo/comfyuimusic, custom workflowjson/workflowpath inputs, outputnode selection, missing model setup, LoRAs, low-VRAM workflow choices, and community workflow imports.
ltx2
AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video.