CC microsoft-docs
Microsoft-ന്റെ ഔദ്യോഗിക ഡോക്യുമെന്റേഷൻ അന്വേഷിച്ച് Azure, .NET, Agent Framework, Aspire, VS Code, GitHub എന്നിവ ഉൾപ്പെടെയുള്ള മേഖലയിലെ ആശയങ്ങൾ, ട്യൂട്ടോറിയലുകൾ, കോഡ് ഉദാഹരണങ്ങൾ എന്നിവ കണ്ടെത്തുക. ഡിഫോൾട്ട് ആയി Microsoft Learn MCP ഉപയോഗിക്കുന്നു; learn.microsoft.com-ന്റെ പുറത്തുള്ള ഉള്ളടക്കങ്ങൾക്ക് Context7യും Aspire MCPയും ഉപയോഗിക്കുന്നു.
The skill promises to search Microsoft's official documentation: Azure, .NET, Agent Framework, Aspire, VS Code, GitHub. Uses Microsoft Learn MCP by default; Context7 and Aspire MCP for content outside learn.microsoft.com.
Audit found high-level code obfuscation—data is encrypted in a way that makes it hard to trace. Content quality scored 72, process score 53. Safety at 82. One file, no scripts, 1407 body tokens. No model runs recorded.
The skill works for documentation lookup, but obfuscation raises transparency concerns. Install if you just need Microsoft Learn access; skip if you need to see what's happening inside.
Microsoft-ന്റെ ഔദ്യോഗിക ഡോക്യുമെന്റേഷൻ അന്വേഷിച്ച് Azure, .NET, Agent Framework, Aspire, VS Code, GitHub എന്നിവ ഉൾപ്പെടെയുള്ള മേഖലയിലെ ആശയങ്ങൾ…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.
Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
-
high Obfuscation
uni-zero-widthSKILL.md:24Zero-width / invisible characters (possible hidden text) (9 occurrences)തിരയൽ കഴിഞ്ഞ്，当需要完整的 ട്യൂട്ടോറിയലുകൾ, എല്ലാ കോൺഫിഗ് ഓപ്ഷനുകളും അല്ലെങ്കിൽ തിരയൽ ഉദ്ധരണികൾ ട്രങ്കേറ്റുചെയ്␀തപ്പോൾ, `microsoft_docs_fetch` ഉപയോഗിക്കുക.
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription 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
- 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
- 100Tools and files. No external tools needed
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1407 tokens
- 100Running it twice. No mutating operations
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 340: 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.