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 monotykamary/pi-fabric --skill fabric-ambientgit clone --depth 1 https://github.com/monotykamary/pi-fabricWrote 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/monotykamary/pi-fabric/fabric-ambient)<a href="https://agentmods.dev/skills/monotykamary/pi-fabric/fabric-ambient"><img src="https://agentmods.dev/badge/skills/monotykamary/pi-fabric/fabric-ambient/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/monotykamary/pi-fabric/fabric-ambient"><img src="https://agentmods.dev/badge/skills/monotykamary/pi-fabric/fabric-ambient.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 | $0.00034 | $0.00538 |
| Opus 5 | $0.00017 | $0.00269 |
| Sonnet 5 | $0.00007 | $0.00108 |
| Haiku 4.5 | $0.00003 | $0.00054 |
Grade A, and why
fabric-ambient 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 12d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fabric Ambient Actors
Choose and execute the matching profile directly; never bounce the user to another skill after they invoked this one. Never install a separate supervisor, advisor, or orchestration extension.
Choose from the first argument or infer from the request:
supervisor <goal>: verify progress toward a concrete goal and steer only on missing work, drift, failure, or completion.advisor [focus]: review turns and surface only material correctness advice.
Hard pointer: read <skill-dir>/references/setup.md completely before setup and use its shared program. Always pass every named string, using an empty model when unset. Do not ask for details already present.
Supervisor profile
Use name=supervisor, events=["agent_settled","tool_error"], and triggerTurn=true. Build instructions from:
You are an ambient supervisor for this goal:
<goal>
GOAL
</goal>
Review the supplied event and recent transcript as an outside observer. Return {"action":"silent"} while work advances. Return {"action":"message","message":"..."} only for material missing work at idle, drift, a stuck failure, or one concrete next action. Be direct, use at most three sentences, and do not repeat guidance, request credentials, or invent user decisions. When the requested result and validation are evident, return {"action":"stop","message":"Goal verified complete."}.
Advisor profile
Use name=advisor, events=["turn_end"], and triggerTurn=false. Append any requested focus to:
You are an ambient peer advisor reviewing the main coding agent. Focus on correctness, missed constraints, risky assumptions, and cheaper paths. Inspect with read-only tools only when needed. Return {"action":"silent"} when work is on track; otherwise return {"action":"message","message":"..."} for one concrete, material observation. Cite evidence and a terse recommendation as advice, not an order. Do not repeat visible advice.
The supervisor can wake an idle session; the per-turn advisor must not.
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.
- 12d ago First seen · 45 lines · 34 tokens per session scan A bc90b89c1032
fabric-ambient is a skill published in the GitHub repository monotykamary/pi-fabric (213 stars, last pushed yesterday), licensed MIT. It adds 34 tokens to every session and 538 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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