SKILLEMALL.ai

CD microsoft-docs

Interoghează documentația oficială Microsoft pentru a găsi concepte, tutoriale și exemple de cod pentru Azure, .NET, Agent Framework, Aspire, VS Code, GitHub și altele. Folosește Microsoft Learn MCP ca implicit, iar pentru conținutul care se află în afara learn.microsoft.com utilizează Context7 și Aspire MCP.

The skillemall take

The skill promises access to Microsoft documentation through MCP integration: Learn, Context7, Aspire for searching Azure, .NET, Agent Framework, and VS Code. In the files—one instruction in Romanian, 1459 body tokens. Quality scored at 72, process at 48. No critical errors found, but half the checks failed: either the description is incomplete or the implementation limps. Not tested on models, not run in sandbox.

For Claude and Cursor it works as a Microsoft-stack reference if you tolerate half the functions potentially running idle. Install only if Microsoft documentation is your primary source and you're ready to verify each query manually.

microsoft/ai-agents-for-beginners Agent Skills author: microsoft MIT 1 file body ≈ 1 459 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Interoghează documentația oficială Microsoft pentru a găsi concepte, tutoriale și exemple de cod pentru Azure, .NET, Agent Framework, Aspire, VS Code, GitHub…

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubVS CodeAzureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 48/100

  • 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. 1 mutating operations with no state check
  • 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 1459 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 310: 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.