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 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/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/nebius/nebius-physical-ai/agent-development"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/agent-development.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 117 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.05444 |
| Opus 5.5 | $0.00016 | $0.02178 |
| Sonnet 5.5 | $0.00008 | $0.01089 |
| Haiku 4.5 | $0.00004 | $0.00544 |
Grade A, and why
agent-development scanned grade A with 1 finding 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 18d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
`subprocess.CompletedProcess` and nonempty report bytes to How it starts
The opening of the file, as written. The whole thing — 376 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.
- 18d ago Changed · +12 lines 1363fe90f5c8
- 1mo ago Changed · +91 lines 35f2efde91c7
- 1mo ago Changed · +13 lines 2fae976577b8
- 1mo 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 (50 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 5,444 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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