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 aiappsgbb/awesome-gbb --skill foundry-agentopsgit clone --depth 1 https://github.com/aiappsgbb/awesome-gbbWrote 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/aiappsgbb/awesome-gbb/foundry-agentops)<a href="https://agentmods.dev/skills/aiappsgbb/awesome-gbb/foundry-agentops"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-agentops/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/aiappsgbb/awesome-gbb/foundry-agentops"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-agentops.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 | $0.00132 | $0.06568 |
| Opus 5 | $0.00066 | $0.03284 |
| Sonnet 5 | $0.00026 | $0.01314 |
| Haiku 4.5 | $0.00013 | $0.00657 |
Grade A, and why
foundry-agentops 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 3d 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 — 476 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Foundry AgentOps adoption
Use native Azure AgentOps to collect reviewable operational evidence for one already deployed agent. This is an instruction/runbook skill, not a wrapper executable, deployment engine, or replacement evidence schema.
Modes and ownership — decide first
- Standalone: analyze existing workflow shape first; generation requires separate user approval of platform, files, triggers, and gates. Never generate workflows merely because Doctor reports them missing.
- Threadlight: detect
specs/manifest.jsonor existing Threadlight conventions in the selected project. Provide AgentOps configuration and prerequisites only: NOworkflow generate, competing pipeline files, adapter, or new manifest.threadlight-cicdowns pipelines; final readiness scoring stays with Threadlight. If ownership is unclear, stop before writing. - Citadel: leave gateway/access contracts, isolation, routing, and rate limits unchanged. Use the existing approved endpoint; never bypass its access path. Do not mutate APIM, networking, RBAC, branch protection, or environment approvals.
- Canonical specialists:
foundry-evalsowns deep evaluators/datasets;foundry-observabilityowns instrumentation;foundry-agtowns AGT authoring and runtime governance. Missing prerequisites are handoffs, not permission to provision resources here. This skill issues no production-ready certification.
1. Select exactly one agent root
Before bootstrap or native analysis, inspect only candidate markers, in order:
- The user's explicit agent root wins; validate it, do not silently substitute.
- Otherwise, a unique
azure.yamlservice withhost: azure.ai.agent: resolve itsprojectpath relative to that manifest (default.). - Otherwise, a unique root containing
.foundry/agent-metadata*.yaml. - Otherwise, an existing
agentops.yamlroot, only if unique.
Multiple candidates at any tier require the user's choice; do not fall through
to a lower tier to hide ambiguity. Multiple agents inside a chosen root also
require an explicit target. With no candidate, request a root; do not initialize
the repository root by default. agentops.yaml is the only opt-in marker:
deployment metadata and .agentops/ alone are discovery hints, not consent.
What ships with it
6 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.
- 3d ago First seen · 476 lines · 132 tokens per session scan A be152cec680b
foundry-agentops is a skill published in the GitHub repository aiappsgbb/awesome-gbb (5 stars, last pushed 3d ago), licensed MIT. It adds 132 tokens to every session and 6,568 once invoked, about $0.0007 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 2026-09-08.
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