Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aiappsgbb/awesome-gbbnpx agentmods add skills/aiappsgbb/awesome-gbb/foundry-observabilityWrote 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-observability)<a href="https://agentmods.dev/skills/aiappsgbb/awesome-gbb/foundry-observability"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-observability.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Privilege Escalation · line 510 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 681 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00231 | $0.11208 |
| Opus 5 | $0.00115 | $0.05604 |
| Sonnet 5 | $0.00046 | $0.02242 |
| Haiku 4.5 | $0.00023 | $0.01121 |
Grade A, and why
foundry-observability 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
"urllib": { "enabled": True }, How it starts
The opening of the file, as written. The whole thing — 805 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Foundry Observability
End-to-end telemetry across every component of a Threadlight pilot: Foundry hosted agent, MCP servers on ACA, ACA jobs (cron triggers), bot service, workspace UI. Default discipline, not optional.
Downstream FinOps consumer.
foundry-cost-monitoringjoins thegen_ai.usage.*spans this skill emits with the Azure Retail Prices API to compute per-agent / per-project / per-tenant cost projection — wire it whenever a FinOps stakeholder needs to answer "what is this agent costing us right now?"
Why this skill exists. Recent pilots deployed cleanly (
azd upreturned 0, all resources provisioned) but App Insights stayed completely empty — no agent traces, no MCP tool calls, no cron logs. Root cause: no one wired the connection at any layer. The intel for each layer lives scattered acrossthreadlight-deploy,foundry-hosted-agents,foundry-mcp-aca,threadlight-event-triggers— but no single skill walks an operator through the full chain. That's what this skill does. Pair withthreadlight-safe-checkStep 5.6 (App Insights existence + first-trace probe) to gate it shut.
Mental model — three layers, one signal
┌─────────────────────────────────────────────────────────────────────┐
│ Layer 3: ACA workloads (MCP / bot / workspace / cron jobs) │
│ • configure_azure_monitor() reads APPLICATIONINSIGHTS_CONNECTION_STRING │
│ • Env var set by Bicep from app-insights.outputs.connectionString │
│ • OTel exporter ships spans + logs + metrics over HTTPS │
└─────────────────────────────────────────────────────────────────────┘
▲
│ direct push from container code
│
┌─────────────────────────────────┼───────────────────────────────────┐
│ Layer 2: Foundry hosted agent (the runtime) │
│ • Account-level AppInsights connection (category: AppInsights) │
│ • Platform AUTO-INJECTS APPLICATIONINSIGHTS_CONNECTION_STRING │
│ • RBAC: Monitoring Metrics Publisher on agent identities │
│ • Tracing emitted by the runtime — no app code change │
└─────────────────────────────────┼───────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────────┐
│ Layer 1: Bicep substrate │
│ • app-insights.bicep — workspace-based (LAW-bound) │
│ • log-analytics.bicep — single LAW for ALL workloads in the RG │
│ • ACA env wiring: dapr.appInsightsConnectionString OR direct env │
│ • Output `connectionString` consumed by every workload │
└─────────────────────────────────────────────────────────────────────┘
What ships with it
14 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.
- references/bicep/aca-env-monitoring.bicep 2.1 KB
- references/bicep/app-insights.bicep 3.4 KB
- references/bicep/log-analytics.bicep 1.5 KB
- references/postprovision/connect_foundry_appinsights.py 7.3 KB runs code
- references/python/__init__.py 68 B runs code
- references/python/kql_probes_aio.py 7.8 KB runs code
- references/python/kql_probes.py 9.0 KB runs code
- references/python/otel_init.py 4.6 KB runs code
- references/queries/agent-traces.kql 1.1 KB
- references/queries/first-trace-probe.kql 1.1 KB
- references/queries/mcp-tool-calls.kql 1.2 KB
- references/queries/silent-cron-debug.kql 1.4 KB
- references/upstream-pin.md 4.0 KB
- test-fixture/consumer_prompt.md 8.6 KB
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 · +2 lines 21c48b255a4d
- 7d ago First seen · 803 lines · 231 tokens per session scan A 74b9070614e8
foundry-observability is a skill published in the GitHub repository aiappsgbb/awesome-gbb (5 stars, last pushed yesterday), licensed MIT. It adds 231 tokens to every session and 11,208 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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