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 agentmods add skills/nebius/nebius-physical-ai/agent-developmentnpx skills add nebius/nebius-physical-ai --skill agent-developmentgit clone --depth 1 https://github.com/nebius/nebius-physical-aiWrote 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/nebius/nebius-physical-ai/agent-development)<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/agent-development"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/agent-development.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.04168 |
| Opus 5 | $0.00020 | $0.02084 |
| Sonnet 5 | $0.00008 | $0.00834 |
| Haiku 4.5 | $0.00004 | $0.00417 |
Grade A, and why
agent-development 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 today.
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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Development (cheap-token chat backend)
How to develop the NPA agent chat backend. For operating a deployed agent
(deploy/bootstrap/verify, chat UX, API grounding, Rerun) use
skills/tools/npa-agent/SKILL.md; for fresh deploy/teardown loops use
skills/workflows/agent-fresh-operate/SKILL.md.
Guiding principle: the cheapest token is the one you never spend. Protect and widen the zero-token grounded path; make the unavoidable model calls small, structured, and cheap-model-first.
Architecture (three layers)
- Grounded intent router (zero tokens) —
npa/src/npa/cli/agent_chat.py.match_chat_intent()classifies a turn;build_grounded_reply()answers from live session state with no model call ("grounded": true). Most operator turns end here. - Cost-tier routing (cheap model calls) —
npa/src/npa/cli/agent_routing.py. Only turns that fall through the router reach Token Factory, and this layer keeps them cheap. - Token Factory client —
npa/src/npa/clients/token_factory.py(operator/SDK path) and the embedded_provider_chat/_chat_with_resilienceinnpa/src/npa/cli/agent.py(agent-VM path).
The embedded-backend mechanism (critical)
The agent VM runs backend.py, which is built as one big f-string inside
_bootstrap_agent_stack in npa/src/npa/cli/agent.py. Pure helper modules are
inlined into it via placeholder substitution — the pattern to reuse when adding
logic:
- Real module (normal Python, no brace escaping):
agent_chat.py,agent_workflow.py,agent_routing.py. - Embed helper
_embedded_agent_<name>_source()strips the docstring +from __future__line. - Placeholder constant
_AGENT_<NAME>_EMBEDappears in the template and is replaced in the.replace(...)chain near the end of_bootstrap_agent_stack.
Rules:
- Put testable logic in a real module and embed it; do not write new logic directly inside the f-string unless it must touch template variables.
- Code written inside the f-string must escape literal braces as
{{/}}and newlines in strings as\\n; substitutions use single{var}. - After editing the template, validate the rendered backend compiles (see
Testing). A stray brace is a
SyntaxErrorat import ofagent.py. - Embedded routes register before the template's own routes. The
_AGENT_*_EMBEDplaceholders sit earlier in the f-string than most@app.*blocks, and Starlette resolves the first matching route, so an embedded module silently wins over a same-path handler written further down inagent.py./artifacts/file/{filename}and/artifacts/downloadeach carried two definitions this way, and the shadowed copies inagent.pywere the weaker ones — noContent-Disposition/nosniffheaders, no run-scoped inventory authorization — so the file a maintainer would open described a contract the deployment did not serve. Before adding a route, grep the embedded modules for its path;test_rendered_backend_registers_no_shadowed_routesfails the build on any method+path registered twice.
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.
- today Changed · +13 lines 2fae976577b8
- 6d ago First seen · 260 lines · 41 tokens per session scan A 72262af8c611
agent-development is a skill published in the GitHub repository nebius/nebius-physical-ai (27 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 4,168 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 2026-08-30.
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