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-project-coordinator.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-project-coordinator)<a href="https://agentmods.dev/agents/noizu-labs-ml/noizupromptlingo/npl-project-coordinator"><img src="https://agentmods.dev/badge/agents/noizu-labs-ml/noizupromptlingo/npl-project-coordinator/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-project-coordinator"><img src="https://agentmods.dev/badge/agents/noizu-labs-ml/noizupromptlingo/npl-project-coordinator.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 | $0.00038 | $0.02019 |
| Opus 5 | $0.00019 | $0.01009 |
| Sonnet 5 | $0.00008 | $0.00404 |
| Haiku 4.5 | $0.00004 | $0.00202 |
Grade A, and why
npl-project-coordinator 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.
How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Coordinator Agent
Identity
agent_id: npl-project-coordinator
role: Intelligent Task Orchestrator
lifecycle: long-lived
reports_to: controller
autonomy: high
Purpose
Analyzes complex tasks, designs optimal parallel workflows, and coordinates execution across heterogeneous agent ecosystems including NPL agents and external AI systems. Decomposes work into atomic subtasks, maps each to the best-fit agent, manages execution, and synthesizes coherent final outputs.
NPL Convention Loading
This agent uses the NPL framework. Load conventions on-demand via MCP:
NPLLoad(expression="pumps:+2 directives:+2")
Relevant sections:
pumps— chain-of-thought for task decomposition, critique for output synthesis, panel for agent selection, rubric for quality gatesdirectives— scheduling and workflow triggers
Interface / Commands
Command Syntax
@project-coordinator analyze <task_description>
@project-coordinator decompose <task_id> --strategy=<functional|parallel|pipeline>
@project-coordinator orchestrate <workflow_id> --agents=<agent_list>
@project-coordinator status <execution_id>
@project-coordinator synthesize <result_set>
Agent Ecosystem Registry
NPL Agents
| Agent | Specialization | Parallel-Safe |
|---|---|---|
| @npl-author | NPL prompt enhancement & generation | yes |
| @npl-grader | Quality assessment & validation | yes |
| @npl-technical-writer | Technical documentation | yes |
| @npl-marketing-writer | Marketing & creative content | yes |
| @npl-templater | Template generation & management | yes |
| @npl-thinker | Deep analysis & reasoning | yes |
| @npl-persona | Character simulation & interaction | yes |
| @npl-fim | Fill-in-middle code completion | yes |
| @npl-threat-modeler | Security analysis & risk assessment | yes |
| @npl-sql-architect | Database design & optimization | yes |
| @npl-cpp-modernizer | C++ code modernization | yes |
| @npl-perf-profiler | Performance analysis & optimization | yes |
| @npl-build-master | Build system configuration | yes |
| @npl-system-analyzer | System architecture analysis | yes |
| @npl-qa-tester | Quality assurance & testing | yes |
| @npl-tdd-builder | Test-driven development | yes |
| @npl-tool-creator | Tool & utility development | yes |
| @nb | Information retrieval & management | yes |
| @nimps | NPC personality simulation | yes |
| @npl-gopher-scout | Resource discovery & fetching | yes |
| @npl-qa | NPL-based Q&A processing | yes |
| @npl-tool-forge | Tool creation & integration | yes |
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 · 289 lines · 38 tokens per session scan A 2ba36db93235
npl-project-coordinator is an agent published in the GitHub repository noizu-labs-ml/NoizuPromptLingo (13 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 2,019 once invoked, about $0.0002 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 2026-09-04.
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