npcpy is a Python library for building applications with multimodal language models, agent-based AI, and knowledge graphs. Researchers and developers use it with local or cloud model providers to create agents, multi-agent teams, and AI workflows.
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 agentmods add skills/npc-worldwide/npcpy/create_jinxnpx skills add NPC-Worldwide/npcpy --skill create_jinxgit clone --depth 1 https://github.com/NPC-Worldwide/npcpyWrote 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/npc-worldwide/npcpy/create_jinx)<a href="https://agentmods.dev/skills/npc-worldwide/npcpy/create_jinx"><img src="https://agentmods.dev/badge/skills/npc-worldwide/npcpy/create_jinx.svg" alt="Measured on agentmods" 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 | $0.00078 | $0.00292 |
| Opus 5 | $0.00039 | $0.00146 |
| Sonnet 5 | $0.00016 | $0.00058 |
| Haiku 4.5 | $0.00008 | $0.00029 |
Grade A, and why
create_jinx 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 6d 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.
What it actually says
create_jinx
Write a new .jinx file from inputs (name, description, inputs spec as JSON list of strings, python body). Agents use this mid-task to crystallize a repeated block of code into a reusable jinx. The jinx is written to the team's jinxes/lib dir by default and registered with the running team so it is immediately callable without a restart.
Inputs
jinx_namedescriptioninputs_spec(default:'[]')python_codetarget_subdir(default:'lib')
Steps
write_jinx→write_jinx.py
Usage
/run_jinx jinx_ref=create_jinx input_values={"jinx_name": "<value>", "description": "<value>", "inputs_spec": "[]", "python_code": "<value>", "target_subdir": "lib"}
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.
- 6d ago First seen · 31 lines · 78 tokens per session scan A 1b696ed8477d
create_jinx is a skill published in the GitHub repository NPC-Worldwide/npcpy (1,497 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 292 once invoked, about $0.0004 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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