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Mag-query sa opisyal na dokumentasyon ng Microsoft upang hanapin ang mga konsepto, tutorial, at mga halimbawa ng code sa iba't ibang serbisyo tulad ng Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, at iba pa. Ginagamit ang Microsoft Learn MCP bilang default, kasama ang Context7 at Aspire MCP para sa nilalamang nasa labas ng learn.microsoft.com.

The skillemall take

This skill queries Microsoft's official documentation—Azure, .NET, Agent Framework, Aspire, VS Code, GitHub—using Microsoft Learn MCP as default, with Context7 and Aspire MCP for content outside learn.microsoft.com.

Quality score 72 against process score 53 signals a gap: the setup functions but incompletely. No critical errors flagged, no medium-level findings either—likely not stress-tested. One file, no scripts. Runs on all platforms from Claude to DeepSeek.

Worth installing if you need IA-assisted access to Microsoft documentation. It works. Nothing more.

microsoft/ai-agents-for-beginners Agent Skills author: microsoft MIT 1 file body ≈ 1 486 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Mag-query sa opisyal na dokumentasyon ng Microsoft upang hanapin ang mga konsepto, tutorial, at mga halimbawa ng code sa iba't ibang serbisyo tulad ng Azure…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubVS CodeAzureAI and agentstype 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
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.
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

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 53/100

  • 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. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 5 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1486 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 354: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 5 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.