nasa-se

nasa-se is a skill for Claude Code from geekatron/jerry. It costs 65 tokens per session (6,406 once invoked), scanned A, original, no licence file.

A systems-engineering skill based on NASA's NPR 7123.1D processes, which describe how to develop and manage complex systems. It coordinates specialized agents for requirements, architecture, verification, risk, reviews, integration, and quality.

In plain words
What is it for?
Use it for requirements engineering, verification and validation, risk management, technical reviews, system integration, configuration management, architecture decisions, trade studies, and quality assurance.
Why use it?
It gives engineering teams a common process for turning needs into a controlled system design and checking that the result works as intended.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the jerry plugin — 32 skills, 2 commands, 89 agents, 6 hooks shipped together

Good fit Use it for requirements engineering, verification and validation, risk management, technical reviews, system integration, configuration management, architecture decisions, trade studies, and quality assurance.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/geekatron/jerry/nasa-se
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 geekatron/jerry --skill nasa-se
Clone the repo
git clone --depth 1 https://github.com/geekatron/jerry

Made for: Claude Code.

Or install jerry, the plugin that ships this one along with the rest of its 32 skills, 2 commands, 89 agents, 6 hooks.

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 nasa-se

README.md
[![agentmods](https://agentmods.dev/badge/skills/geekatron/jerry/nasa-se/github.svg)](https://agentmods.dev/skills/geekatron/jerry/nasa-se)
Your own site
<a href="https://agentmods.dev/skills/geekatron/jerry/nasa-se"><img src="https://agentmods.dev/badge/skills/geekatron/jerry/nasa-se/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 nasa-se

Your own site · 80×15
<a href="https://agentmods.dev/skills/geekatron/jerry/nasa-se"><img src="https://agentmods.dev/badge/skills/geekatron/jerry/nasa-se.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,406 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 $0.00065 $0.06406
Opus 5 $0.00032 $0.03203
Sonnet 5 $0.00013 $0.01281
Haiku 4.5 $0.00006 $0.00641

Measured 9d ago against content hash 07859ce31ad8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

nasa-se 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 9d 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/nasa-se/SKILL.md · 561 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

56 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. 9d ago First seen · 561 lines · 65 tokens per session scan A 07859ce31ad8

Subscribe to this mod's changes

nasa-se is a skill published in the GitHub repository geekatron/jerry (33 stars, last pushed today), with no licence file. It adds 65 tokens to every session and 6,406 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.

Related

Other skills, from other repositories

fastapi

FastAPI best practices + Pydantic. Use when building or reviewing FastAPI APIs.

martineserios/thebrana · 21 tokens

domain-driven-design

DDD tactical patterns for complex business modeling including entities, value objects, aggregates, domain services, repositories, specifications, and bounded contexts. Python dataclass implementations with TypeScript alternatives. Use when building rich domain models, enforcing invariants, or separating domain logic…

martineserios/thebrana · 57 tokens

research-extraction

Deep extraction of research corpora into structured knowledge documents using a Workflow-driven subagent/reviewer pattern. Use when you have raw source documents (theses, papers, reports) and need structured extraction across multiple axes (architecture, messages, algorithms, forms, etc.) with confidence-annotated…

geronimo-iia/agent-skills · 87 tokens

networkx

Create, analyze, and visualize complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph…

userInner/SKILLS · 83 tokens

biopython

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use…

userInner/SKILLS · 76 tokens

cirq

Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for…

userInner/SKILLS · 67 tokens