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 kangarooking/director-skills --skill emotion-performance-directorgit clone --depth 1 https://github.com/kangarooking/director-skillsWrote 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/kangarooking/director-skills/emotion-performance-director)<a href="https://agentmods.dev/skills/kangarooking/director-skills/emotion-performance-director"><img src="https://agentmods.dev/badge/skills/kangarooking/director-skills/emotion-performance-director/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/kangarooking/director-skills/emotion-performance-director"><img src="https://agentmods.dev/badge/skills/kangarooking/director-skills/emotion-performance-director.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 | $0.00101 | $0.01920 |
| Opus 5.5 | $0.00040 | $0.00768 |
| Sonnet 5.5 | $0.00020 | $0.00384 |
| Haiku 4.5 | $0.00010 | $0.00192 |
Grade A, and why
emotion-performance-director 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 13d 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 — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Emotion Performance Director
Purpose
Turn abstract emotional intent into AI-video-executable human performance.
The skill does not merely label emotion. It describes how emotion becomes visible and audible through behavior over time.
Core formula:
Subtext → key performance signals → temporal order → afterbeat
Where performance signals are selected only as needed from:
gaze / breath / face / body / voice
Do not force every channel into every prompt.
Core Principles
-
Subtext drives performance. Infer what the character wants, resists, hides, or cannot fully control. Do not generate from the emotion label alone.
-
Describe observable behavior, not abstract emotion words. Prefer “her jaw tightens and her voice drops” over “she becomes very angry.”
-
Use the fewest signals that make the emotion legible. Normally select 2–4 dominant signals from gaze, breath, face, body, and voice. If removing a gesture does not weaken the performance, remove it.
-
Emotion unfolds in time. Organize the performance as:
- before the line
- during the line
- after the line
-
Preserve one psychological cause. Gaze, breath, facial tension, posture, and voice should feel like different consequences of the same internal state, not a collection of unrelated acting tricks.
-
Default to naturalistic screen acting. Favor restrained micro-reactions, slight delays, incomplete gestures, and residual reactions after speech. Avoid theatrical overacting unless the user explicitly requests it.
Input Handling
Minimum usable input:
- dialogue or intended action
- emotional intent
Optional context may include:
- relationship between characters
- immediate trigger or situation
- subtext
- desired restraint/intensity
- POV or eyeline target
- existing full video prompt
Do not require the user to provide structured parameters when natural-language context is sufficient.
If the user provides an existing video prompt, modify only the emotional-performance layer unless asked to change other elements.
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.
- 13d ago First seen · 219 lines · 101 tokens per session scan A 19bdb8ffe3a3
emotion-performance-director is a skill published in the GitHub repository kangarooking/director-skills (215 stars, last pushed today), licensed MIT. It adds 101 tokens to every session and 1,920 once invoked, about $0.0004 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 2026-10-08.
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