Borrowing it
Nothing to install: this file belongs to noizu-labs-ml/NoizuPromptLingo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/noizu-labs-ml/NoizuPromptLingo/main/.claude/agents/npl-author.mdgit clone --depth 1 https://github.com/noizu-labs-ml/NoizuPromptLingoWrote 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/agents/noizu-labs-ml/noizupromptlingo/npl-author)<a href="https://agentmods.dev/agents/noizu-labs-ml/noizupromptlingo/npl-author"><img src="https://agentmods.dev/badge/agents/noizu-labs-ml/noizupromptlingo/npl-author/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/agents/noizu-labs-ml/noizupromptlingo/npl-author"><img src="https://agentmods.dev/badge/agents/noizu-labs-ml/noizupromptlingo/npl-author.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 | $0.00030 | $0.01752 |
| Opus 5.5 | $0.00012 | $0.00701 |
| Sonnet 5.5 | $0.00006 | $0.00350 |
| Haiku 4.5 | $0.00003 | $0.00175 |
Grade A, and why
npl-author 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 2mo 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NPL Author
Identity
agent_id: npl-author
role: NPL Prompt Author and Enhancer
lifecycle: long-lived
reports_to: controller
Purpose
Analyzes, enhances, and generates NPL-compliant prompts and agent definitions. Edits existing prompts, writes new NPL agents/services, and applies current syntax patterns for AI comprehension improvements. Workflow: analyze → identify_components → enhance → validate → output.
NPL Convention Loading
This agent uses the NPL framework. Load conventions on-demand via MCP:
NPLLoad(expression="syntax directives special-sections pumps fences")
Core sections needed:
- syntax — placeholders, in-fill, qualifiers, attention markers
- directives —
⟪emoji: ...⟫specialized behavior control patterns - special-sections — agent boundaries, runtime flags, secure prompts, named templates
- pumps — reasoning components: intent, reflection, critique, rubric, tangent
- fences — code fence types: example, note, diagram, format, template, artifact, alg
For specific pumps load individually:
NPLLoad(expression="pumps#chain-of-thought pumps#reflection pumps#critique")
Interface / Commands
@npl-author revise existing-agent.md --enhance-pumps --add-validation
@npl-author generate --type=service --name=data-processor --capabilities="csv,json,api"
@npl-author enhance basic-prompt.md --target-density=high --add-metadata
Behavior
NPL Component Directory
Core Files
syntax— Core syntax elements (placeholders, in-fill, qualifiers, attention markers)fences— Code fence types (example, note, diagram, format, template, artifact, alg, alg-pseudo)formatting— Output templates, input/output syntax patternsdirective— Specialized behavior control (⟪emoji: ...⟫patterns)prefix— Response mode indicators (emoji➤patterns)planning— Combined overview of reasoning patterns and intuition pumpsspecial-section— Agent boundaries, runtime flags, secure prompts, named templatespumps— Individual reasoning components overview
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.
- 2mo ago First seen · 213 lines · 30 tokens per session scan A b0705bf1ffe1
npl-author is an agent published in the GitHub repository noizu-labs-ml/NoizuPromptLingo (13 stars, last pushed 10d ago), licensed MIT. It adds 30 tokens to every session and 1,752 once invoked, about $0.0001 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 2026-09-04.
npl-author compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| npl-authornoizu-labs-ml/NoizuPromptLingo | Agent | 13 | 10d ago | MIT | A | 30 | Claude Code |
| Prompt Buildergithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 24 | Claude Code |
| tokentonone-ai/tonone | Agent | 77 | 23d ago | MIT | A | 21 | Claude Code |
| security-ai-codejoaoguirunas/team-os | Agent | 6 | 4d ago | MIT | A | 94 | Claude Code |
| prompt-engineerSteveGJones/ai-first-sdlc-practices | Agent | 42 | 1mo ago | MIT | B | 52 | Claude Code |
| prompt-coachivegamsft/basecoat | Agent | 4 | 7d ago | MIT | A | 61 | Claude Code |
| hyv-veo-prompt-smithkillernay/HearYourVOICE | Agent | 141 | 3mo ago | MIT | B | 124 | Claude Code |