npcpy-prompting

npcpy-prompting is a skill for Claude Code, Codex from NPC-Worldwide/npcsh. It costs 16 tokens per session (634 once invoked), scanned A, original, MIT.

A reference guide for using npcpy, a Python library for sending prompts to language models and receiving formatted responses. It covers imports, ordinary calls, JSON responses, streaming, and reusable model settings.

In plain words
What is it for?
Use it to make basic and streaming model calls, request JSON output, create an NPC configuration object, and pass conversation history or sampling options.
Why use it?
It prevents common integration mistakes, such as passing arguments in the wrong form, calling the wrong interface, or parsing a response twice.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to make basic and streaming model calls, request JSON output, create an NPC configuration object, and pass conversation history or sampling options.

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Install with agentmods
npx agentmods add skills/npc-worldwide/npcsh/npcpy-prompting
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 NPC-Worldwide/npcsh --skill npcpy-prompting
Clone the repo
git clone --depth 1 https://github.com/NPC-Worldwide/npcsh

Made for: Claude Code, Codex.

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README.md
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Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 634 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original 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 $0.00016 $0.00634
Opus 5 $0.00008 $0.00317
Sonnet 5 $0.00003 $0.00127
Haiku 4.5 $0.00002 $0.00063

Measured 10d ago against content hash fb383368de3b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

npcpy-prompting 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 10d 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/npcpy-prompting/SKILL.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

npcpy-prompting

npcpy LLM prompting and JSON formatting patterns.

Imports

Always import at module level:

  • from npcpy.llm_funcs import get_llm_response
  • from npcpy.npc_compiler import NPC
  • from npcpy.gen.response import get_litellm_response (only for streaming)

Basic-Call

get_llm_response(prompt, model, provider, **kwargs) — first arg is POSITIONAL. Do NOT write prompt=prompt. Do NOT use NPC.call(). The function is module-level.

Json-Mode

Pass format="json" for structured output. npcpy parses internally. Access via response["response"]. Never call json.loads() manually.

Npc-Object

Create an NPC to hold model, provider, and primary_directive. Pass it as npc=npc_instance so npcpy reads those values:

npc = NPC(name="...", primary_directive="...", model="...", provider="...")
response = get_llm_response(prompt, npc=npc, format="json", temperature=0.7)
data = response["response"]

Messages

Pass conversation history as messages=[{"role": "system", "content": msg}]. This is a kwarg like any other. It does not persist between calls.

Parameters

Sampling kwargs to get_llm_response:

  • temperature, top_p, top_k, max_tokens
  • stream=True returns a generator in response["response"]

Streaming

For token-level streaming use get_litellm_response with stream=True. For segment-level use get_llm_response(..., stream=True) and iterate response["response"].

Anti-Patterns

  • Do NOT use json.loads(response["response"]).
  • Do NOT call response.get("response") and then parse it again.
  • Do NOT assume response is a string when format="json" is used.

Prompt-Formatting

When constructing prompt strings in Python:

  • Use f"""...""" for all multiline prompts. Do NOT use implicit string concatenation.
  • Do NOT put multiline strings directly in a return statement. Assign to a variable first, then return it.
  • The closing """ must be at the same indentation as the variable assignment.
  • Do NOT escape braces as {{ inside f-strings. If you need literal curly braces in the prompt output, use explicit string concatenation:
    prompt = f"""Write a JSON response like this:""" + """\n{'key': 'value'}\n"""
    
  • Never use f"..." f"..." on adjacent lines or in parentheses expecting the parser to concatenate them.

Read the full file on GitHub · 81 lines

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. 10d ago First seen · 81 lines · 16 tokens per session scan A fb383368de3b

Subscribe to this mod's changes

npcpy-prompting is a skill published in the GitHub repository NPC-Worldwide/npcsh (478 stars, last pushed today), licensed MIT. It adds 16 tokens to every session and 634 once invoked, about $0.0001 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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