DD deploying-scalable-agents
Dalhin ang isang gumaganang prototype ng agent sa isang scalable, observable na production deployment sa Microsoft Foundry. Saklaw nito ang mga deployment pattern (client-hosted, hosted agents, agent workflows), ang lifecycle ng agent, model routing, response caching, evaluation gates, human-in-the-loop approval, observability gamit ang OpenTelemetry, cost optimisation, at smoke-testing ng mga deployed na agent gamit ang AI Smoke Test action. Batay sa Lesson 16 ng AI Agents for Beginners. GAMITIN PARA SA: pag-deploy ng agent sa production, pag-scale ng agent, Microsoft Foundry hosted agent, Foundry Agent Service, model routing, response caching, evaluation gate, release gate, human approval workflow, agent observability, agent tracing, agent cost optimisation, smoke test ng hosted agent, production customer support agent. HUWAG GAMITIN PARA SA: pagbuo ng iyong unang agent (simulan sa Lesson 01), pagpapatakbo ng mga agent nang lokal sa device (gamitin ang local-ai-agents / Lesson 17), Azure infrastructure provisioning na hindi kaugnay sa mga agent, mga deployment target na hindi sa Foundry.
Dalhin ang isang gumaganang prototype ng agent sa isang scalable, observable na production deployment sa Microsoft Foundry.
As a process D 38/100 · Unfinished process — References files that are not bundled: ../../../16-deploying-scalable-agents/README.md, ../../../16-deploying-scalable-agents/code_samples/16-python-agent-framework.ipynb, ../../../../../.github/workflows/smoke-test.yml
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Shorten the description to 1024 characters.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1106 chars, limit 1024 - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: ../../../16-deploying-scalable-agents/README.md - warning
missing-refreference to a missing file: ../../../16-deploying-scalable-agents/code_samples/16-python-agent-framework.ipynb - warning
missing-refreference to a missing file: ../../../../../.github/workflows/smoke-test.yml - warning
missing-refreference to a missing file: ../../../tests/README.md
Process rating: all ten parameters 38/100
- 0Tools and files. 4 referenced file(s) missing: ../../../16-deploying-scalable-agents/README.md, ../../../16-deploying-scalable-agents/code_samples/16-python-agent-framework.ipynb, ../../../../../.github/workflows/smoke-test.yml
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 19 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 23 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1638 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1106: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +4Structure: 10 headings
- +3Step-by-step instructions: 23 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 29.