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 skills add LordMoMA/AI_skills --skill nasa-codegit clone --depth 1 https://github.com/LordMoMA/AI_skillsWrote 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/lordmoma/ai_skills/nasa-code)<a href="https://agentmods.dev/skills/lordmoma/ai_skills/nasa-code"><img src="https://agentmods.dev/badge/skills/lordmoma/ai_skills/nasa-code/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/skills/lordmoma/ai_skills/nasa-code"><img src="https://agentmods.dev/badge/skills/lordmoma/ai_skills/nasa-code.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 | $0.00058 | $0.01097 |
| Opus 5.5 | $0.00023 | $0.00439 |
| Sonnet 5.5 | $0.00012 | $0.00219 |
| Haiku 4.5 | $0.00006 | $0.00110 |
Grade A, and why
nasa-code 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 1mo 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 1mo ago First seen · 108 lines · 58 tokens per session scan A de6631d4c9bd
nasa-code is a skill published in the GitHub repository LordMoMA/AI_skills (19 stars, last pushed 5mo ago), with no licence file. It adds 58 tokens to every session and 1,097 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
ai-architect-review
Review the architecture of a system that calls a language model. Use when adding an agent loop, a retrieval path, a tool surface, or an MCP server to a codebase; when a system that worked in a demo is being prepared for production; or when asked to audit, review, or plan AI/agent architecture. Checks the four…
github-code-review
Comprehensive GitHub pull-request code review with multi-agent coordination. Use when reviewing a PR or diff, auditing changes for correctness/security/style before merge, or generating actionable inline review comments.
code-review
Structured code reviews with severity-ranked findings and deep multi-agent mode. Use when performing a code review, auditing code quality, or critiquing PRs, MRs, or diffs, including a diff or patch pasted inline. For the full multi-agent workflow, use the ia-review command (/ia-review in Claude Code).
receiving-code-review
Process code review feedback critically: check correctness before acting, push back on incorrect suggestions, no performative agreement. Use when responding to PR/MR review comments or implementing reviewer suggestions received from others.
santa-method
Send a finished change to two reviewers who did not write it, using one rubric, and stop after three rounds. Use before a public page, a priced artifact, or a pull request that changes behavior.
security-review
Scan a port or a diff before it lands, and apply the narrow deny list for this machine. Use before copying upstream skills, hooks, or commands into a repo or into the live Claude directory.