SKILLEMALL.ai

BD customizations-in-the-agent-host

Architecture and hard-won debugging lessons for customization enablement (plugins, MCP servers, agents, skills, instructions) in the agent host. Use when changing how customizations are discovered, published, enabled/disabled, or handed to a provider SDK; when a customization shows the wrong enabled state in the UI; or when a disabled MCP server or plugin is still reaching the model.

The skillemall take

A skill covering the architecture of the customization system in an agent host—plugins, MCP servers, instructions. Promises help when debugging the enable/disable logic and passing extensions to a provider SDK.

One file, 2184 tokens, no scripts. Scores: quality 84, safety 100. No critical findings, linter passes. No model run, no sandbox test. Reads like a reference guide to internals rather than a ready-made tool for quick fixes.

Install if you're digging into customization guts and need a map. If you're just adding a plugin—skip it.

microsoft/vscode Agent Skills author: microsoft MIT 1 file body ≈ 2 184 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Architecture and hard-won debugging lessons for customization enablement (plugins, MCP servers, agents, skills, instructions) in the agent host.

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAzureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
45/100
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

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 45/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 11 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 100Steps. 23 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2184 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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 386: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 23 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.