ning-hao-black-comedy

ning-hao-black-comedy is a skill for Claude Code, Codex from fanchengchen1-collab/super-director. It costs 68 tokens per session (275 once invoked), scanned A, original, no licence file.

A writing guide for grounded black comedy about ordinary people caught in small-scale crime, misunderstandings, and chains of cause and effect. It draws on publicly documented creative principles associated with Ning Hao without copying his specific films.

In plain words
What is it for?
Use it to design crime farces, escalating misunderstandings, connected plotlines, and tightly structured short-drama stories.
Why use it?
It helps combine realistic local detail with absurd situations while keeping a complicated short-drama plot controlled. It is useful when several storylines need to collide in a believable way.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the super-director plugin — 13 skills shipped together

Good fit Use it to design crime farces, escalating misunderstandings, connected plotlines, and tightly structured short-drama stories.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/fanchengchen1-collab/super-director/ning-hao-black-comedy
Install

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.

Any agent
npx skills add fanchengchen1-collab/super-director --skill ning-hao-black-comedy
Clone the repo
git clone --depth 1 https://github.com/fanchengchen1-collab/super-director

Made for: Claude Code, Codex.

Or install super-director, the plugin that ships this one along with the rest of its 13 skills.

Wrote 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.

agentmods badge for ning-hao-black-comedy

README.md
[![agentmods](https://agentmods.dev/badge/skills/fanchengchen1-collab/super-director/ning-hao-black-comedy/github.svg)](https://agentmods.dev/skills/fanchengchen1-collab/super-director/ning-hao-black-comedy)
Your own site
<a href="https://agentmods.dev/skills/fanchengchen1-collab/super-director/ning-hao-black-comedy"><img src="https://agentmods.dev/badge/skills/fanchengchen1-collab/super-director/ning-hao-black-comedy/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.

agentmods 80×15 button for ning-hao-black-comedy

Your own site · 80×15
<a href="https://agentmods.dev/skills/fanchengchen1-collab/super-director/ning-hao-black-comedy"><img src="https://agentmods.dev/badge/skills/fanchengchen1-collab/super-director/ning-hao-black-comedy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 275 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00068 $0.00275
Opus 5 $0.00034 $0.00138
Sonnet 5 $0.00014 $0.00055
Haiku 4.5 $0.00007 $0.00028

Measured 12d ago against content hash ac9b1b1cd067, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ning-hao-black-comedy 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.

skills/ning-hao-black-comedy/SKILL.md · 29 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

3 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.

Changes

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.

  1. 12d ago First seen · 29 lines · 68 tokens per session scan A ac9b1b1cd067

Subscribe to this mod's changes

ning-hao-black-comedy is a skill published in the GitHub repository fanchengchen1-collab/super-director (14 stars, last pushed 1mo ago), with no licence file. It adds 68 tokens to every session and 275 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 2026-08-30.

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