AC outlook-email
Manage Outlook and Microsoft 365 email with AI agents — triage inbox by sender trust, draft replies with tone matching, organize folders, create inbox rules, and monitor for priority messages. Use when user says "check my email," "triage inbox," "organize email," "email cleanup," "outlook folders," "inbox rules," "draft a reply," "email summary," "unread messages," "email heartbeat," or "monitor my mailbox." Works with any Graph API client; optionally enhanced by the open-source email-agent-mcp server.
As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
How to improve
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "requires"
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
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 75 mutating operations with no state check
- 40Consistency. Frontmatter name (outlook-email) differs from the folder (outlook-email-management)
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Failures and branches. 7 branches
- 70Execution cost. Instruction body is 4509 tokens
- 100Steps. 49 steps
- 100When it triggers. States when to use and when not to
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 11 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 11 example trigger phrases
- +3Description length 507: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 49 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.