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-run-data-collectiongit 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-run-data-collection)<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/agent-run-data-collection"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/agent-run-data-collection/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-run-data-collection"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/agent-run-data-collection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00049 | $0.01748 |
| Opus 5 | $0.00024 | $0.00874 |
| Sonnet 5 | $0.00010 | $0.00350 |
| Haiku 4.5 | $0.00005 | $0.00175 |
Grade A, and why
agent-run-data-collection 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Run Data Collection
Collect complete, replayable agent trajectories without making telemetry a new source of fabricated success or lost operator work.
Required runtime configuration
Resolve these from owner-only runtime configuration; never commit their values:
NPA_AGENT_DATASET_TENANT_ID: exact tenant that owns the destination.NPA_AGENT_DATASET_URI: exacts3://<bucket>/<prefix>dataset root.- Existing NPA S3 endpoint and credentials for that bucket. Do not copy secrets into a trajectory, command line, workflow spec, log, or skill file.
Before enabling collection, verify the active agent deployment reports the same tenant and that the destination bucket is a writable resource in that tenant. Pass the verified active tenant and authorized dataset bucket to the emitter; empty identity arguments fail closed. S3 access alone does not establish bucket ownership: retain the provider ownership and deployment identity proof privately. Tenant-wide discovery alone does not authorize cross-project writes. Do not create a bucket, grant IAM, or change tenant/project configuration unless the operator separately requests it.
Collection hierarchy and episode boundary
Use three levels:
- Session: the whole conversation or operator work period.
- Episode: one accepted goal pursued until objective success, failure, refusal, cancellation, or an explicit handoff. Follow-up messages that refine the same unfinished goal stay in the episode; a materially new goal starts a new episode.
- Event: each prompt, plan, model decision, tool call, observation, confirmation, retry, correction, or final response inside an episode.
The episode is the dataset row. Assign its id when the goal is accepted and
finalize exactly one npa.agent.trajectory.v1 record at the terminal boundary.
Link it to its parent session and include all nested events; do not create a
separate dataset row for every chat turn or tool call.
Preamble integration
Link the skill explicitly from the agent preamble. Use this canonical line:
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.
- 2d ago Changed · +45 lines eb74b25c938a
- 10d ago First seen · 116 lines · 49 tokens per session scan A 6ad31fe7afa9
agent-run-data-collection is a skill published in the GitHub repository nebius/nebius-physical-ai (27 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 1,748 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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