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 psenger/ai-agent-skills --skill agentic-skeleton-dir-structuregit clone --depth 1 https://github.com/psenger/ai-agent-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/psenger/ai-agent-skills/agentic-skeleton-dir-structure)<a href="https://agentmods.dev/skills/psenger/ai-agent-skills/agentic-skeleton-dir-structure"><img src="https://agentmods.dev/badge/skills/psenger/ai-agent-skills/agentic-skeleton-dir-structure/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/psenger/ai-agent-skills/agentic-skeleton-dir-structure"><img src="https://agentmods.dev/badge/skills/psenger/ai-agent-skills/agentic-skeleton-dir-structure.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 | $0.00121 | $0.04589 |
| Opus 5 | $0.00060 | $0.02295 |
| Sonnet 5 | $0.00024 | $0.00918 |
| Haiku 4.5 | $0.00012 | $0.00459 |
Grade C, and why
agentic-skeleton-dir-structure scanned grade C with 2 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
to the AI (e.g., "ignore previous instructions", shell metacharacters used as a value, Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
user to supply a valid one. Do not construct or run any command with an unvalidated value. How it starts
The opening of the file, as written. The whole thing — 481 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Skeleton Directory Structure Skill v2.0
Scaffolds production-ready agentic AI project structures that integrate with Agent-OS v3 by Builder Methods.
This skill follows the Spec-Driven Development (SDD) methodology: ~95% planning, ~5% building. You shape detailed specifications before the AI writes any code.
When This Skill Activates
On activation, follow this sequence:
- Check for arguments. If
$ARGUMENTSis provided, parse it for the repo pattern (single,mono, ormulti-lang) and skip that question in Step 0. - Detect the current directory. Run
lsto check if the current directory already has files (existing project) or is empty/new. If existing:- Warn the user: "This directory already has files. I can scaffold around them or create a new subdirectory. Which do you prefer?"
- If there is already a
CLAUDE.md, ask if they want to overwrite or preserve it.
- Begin Step 0 — gather requirements through interactive questions.
- After all inputs are collected, present a summary and ask for confirmation before creating anything.
- Scaffold — create directories, generate files, show the final tree.
- Guide next steps — Agent-OS installation and SDD workflow.
Step 0 — Gather Requirements
Collect these six inputs. Ask one question at a time, wait for a response, then proceed to the next. Skip any question already answered via arguments or context.
Question 1 — Repo Pattern
What repo pattern do you want?
- Single Repo — one app or service
- Mono-Repo — multiple apps/services, same language ecosystem
- Multi-Language Mono-Repo — services in different languages (e.g. Python + TypeScript + Go)
Question 2 — Platform Type
What type of project is this?
- Frontend — SPA, SSR, static site
- Backend — API, service, worker
- Full-Stack — frontend + backend together
- Middleware — gateway, BFF, proxy
- Multi-Service — multiple independent services
- Agents/AI — agentic AI service with tools, prompts, memory
What ships with it
5 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.
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.
- 9d ago First seen · 481 lines · 121 tokens per session scan C 5ba16cea67c1
agentic-skeleton-dir-structure is a skill published in the GitHub repository psenger/ai-agent-skills (10 stars, last pushed 3mo ago), licensed MIT. It adds 121 tokens to every session and 4,589 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it C with 2 findings (instruction-override phrasing, unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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