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AC azure-resource-manager-cosmosdb-dotnet

Azure Resource Manager SDK for Cosmos DB in .NET. Use for MANAGEMENT PLANE operations: creating/managing Cosmos DB accounts, databases, containers, throughput settings, and RBAC via Azure Resource Manager. NOT for data plane operations (CRUD on documents) - use Microsoft.Azure.Cosmos for that. Triggers: "Cosmos DB account", "create Cosmos account", "manage Cosmos resources", "ARM Cosmos", "CosmosDBAccountResource", "provision Cosmos DB".

microsoft/skills Agent Skills author: microsoft MIT 4 files body ≈ 1 983 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Azure Resource Manager SDK for Cosmos DB in .NET. Use for MANAGEMENT PLANE operations: creating/managing Cosmos DB accounts, databases, containers, throughput…

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

IntegrationAzureInfrastructuretype 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
A
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
98
Run on models
none yet
Process rating
C
62/100
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

    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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 62/100

    • 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
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1983 tokens
    • 100Running it twice. Mutating operations check current state
    • low 10 top-level sections: this looks like several domains in one skill

    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

    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 441: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 98.