SKILLEMALL.ai
GitHub ↗ RU Sign in

AC office365-connector

Office 365 / Outlook connector for email (read/send), calendar (read/write), and contacts (read/write) using resilient OAuth authentication. NOW WITH MULTI-ACCOUNT SUPPORT! Manage multiple Microsoft 365 identities from a single skill. Solves the difficulty connecting to Office 365 email, calendar, and contacts. Uses Microsoft Graph API with comprehensive Azure App Registration setup guide. Perfect for accessing your Microsoft 365/Outlook data from OpenClaw.

modbender/skill-library-mcp Agent Skills author: modbender MIT 13 files body ≈ 3 335 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Office 365 / Outlook connector for email (read/send), calendar (read/write), and contacts (read/write) using resilient OAuth authentication.

As a process C 64/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting

GeneratorAzureOutlookPersonal productivitytype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
99
Quality 40%
76
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token references/setup-guide.md:71
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Example: `AbC1~dEf2…Cd0`
    quoted

Files scanned: 13. 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 64/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 81 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3335 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 19 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

  • +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 461: enough signal without eating the budget
  • +4Structure: 47 headings
  • +3Step-by-step instructions: 81 items
  • +4Has examples (20 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.