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DF deploying-scalable-agents

Membawa prototaip agen yang berfungsi ke pelaksanaan pengeluaran yang boleh diskala dan boleh diperhatikan di Microsoft Foundry. Meliputi corak pelaksanaan (agen dihoskan oleh pelanggan, agen dihoskan, aliran kerja agen), kitaran hayat agen, pengarahan model, penampan respons, pintu penilaian, kelulusan manusia dalam kitaran, kebolehamatan dengan OpenTelemetry, pengoptimuman kos, dan ujian asap agen yang dilaksanakan dengan tindakan Ujian Asap AI. Berdasarkan Pelajaran 16 AI Agents for Beginners. GUNA UNTUK: melaksanakan agen ke pengeluaran, menskala agen, agen yang dihoskan Microsoft Foundry, Perkhidmatan Agen Foundry, pengarahan model, penampan respons, pintu penilaian, pintu pelepasan, aliran kerja kelulusan manusia, kebolehamatan agen, penjejakan agen, pengoptimuman kos agen, ujian asap agen yang dihoskan, agen sokongan pelanggan pengeluaran. JANGAN GUNA UNTUK: membina agen pertama anda (mulakan dengan Pelajaran 01), menjalankan agen secara tempatan pada peranti (gunakan local-ai-agents / Pelajaran 17), penyediaan infrastruktur Azure yang tidak berkaitan dengan agen, sasaran pelaksanaan bukan Foundry.

microsoft/ai-agents-for-beginners Agent Skills author: microsoft 1 file body ≈ 1 515 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Membawa prototaip agen yang berfungsi ke pelaksanaan pengeluaran yang boleh diskala dan boleh diperhatikan di Microsoft Foundry.

As a process F 33/100 · No process to follow — 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

ProcedureAzureGitHubAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
D
72/100
safety, quality, tests
Safety 60%
100
Quality 40%
29
Run on models
none yet
Process rating
F
33/100
No process to follow
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
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. Shorten the description to 1024 characters.
  3. The text references files that are not there: add them or drop the references.
For the model run — optional
  • 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-long description is 1122 chars, limit 1024
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: ../../../16-deploying-scalable-agents/README.md
  • warning missing-ref reference to a missing file: ../../../16-deploying-scalable-agents/code_samples/16-python-agent-framework.ipynb
  • warning missing-ref reference to a missing file: ../../../../../.github/workflows/smoke-test.yml
  • warning missing-ref reference to a missing file: ../../../tests/README.md

Process rating: all ten parameters 33/100

Will not run. 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
  • 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
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1515 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 1122: 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.