Agents & OrchestrationSûr100100/100
Pattern Radar (Microsoft)
Scan the user's recent Microsoft 365 signals (emails, active chats/channels, calendar subjects) to surface recurring patterns worth productizing — either as a blog post (the user explains the same thing repeatedly) or as an automation (the user does the same multi-step task repeatedly). Use when the user asks "what should I write about?", "what could I automate?", "find patterns in my work", or invokes "/pattern-radar".
ou envoie-le directement à ton agent.
Installer dans ton projet
$ curl -fsSL https://arboristhree.xyz/cli/install-skill.mjs -o /tmp/arboris-install-skill.mjs && node /tmp/arboris-install-skill.mjs pattern-radar__microsoft-cat-agent-skills__submissions-d8aa62ee163bMicrosoft
microsoft/cat-agent-skills
Contenu à copier
--- name: pattern-radar description: Scan the user's recent Microsoft 365 signals (emails, active chats/channels, calendar subjects) to surface recurring patterns worth productizing — either as a blog post (the user explains the same thing repeatedly) or as an automation (the user does the same multi-step task repeatedly). Use when the user asks "what should I write about?", "what could I automate?", "find patterns in my work", or invokes "/pattern-radar". metadata: origin: Microsoft --- # Pattern Radar Find recurring patterns in the user's recent work signals that could be turned into leverage — a **blog post** (the user keeps explaining the same thing) or an **automation** (the user keeps doing the same manual, multi-step task). Give blog and automation candidates equal weight; bias toward automation candidates, since offloading repetitive work is usually the bigger win. Default lookback window: **the last 7 days** from the current date/time. Treat the provided current datetime as authoritative — never reason from training-data dates. > **Tool names.** This skill refers to Microsoft 365 tools as `m365_*`. If your > host exposes them under different names, map them to the equivalent capability. ## Inputs — collect breadth, not depth 1. **Email** — list Inbox and Sent from the last 7 days (subjects + first-line previews only; do not open bodies). **Pay special attention to Sent items**: they reveal the user's own repeated outbound actions (forwards, intros, status pings, FYIs, "looping in X" handoffs, RSVPs, reschedules). 2. **Active chats** — list recent chats; for each chat the user has posted in over the last ~30 days, fetch the last 7 days of messages. Strip @-mention noise. 3. **Active channels** — for channels the user has posted in over the last ~30 days, fetch the last 7 days of messages. Skip silent channels. 4. **Calendar** — list events from the last 7 days (**subjects only** — no bodies, no attendee lists). Look for repeated reschedules, repeated tentative responses, recurring conflict patterns, and meeting-prep cadences. ## Clustering — what counts as a pattern A signal qualifies only if it appears **≥3 times across ≥2 distinct people / chats / customers / threads / events** in the window. Be ruthless — one-offs are noise. **Blog cluster types** - **Repeated explanation** — the user answers the same question or explains the same concept to 3+ different people. → blog candidate. - **Recurring FAQ** — the same question shows up in 3+ chats/channels from different askers. → blog / FAQ candidate. **Automation cluster types (cast a wide net)** - **Repeated multi-step manual task** — the same sequence of clicks / drafts / file moves / API calls, repeatedly. → automation candidate. - **Repeated handoff / triage** — forwarding, "looping in", or intro'ing the same kinds of items to the same people 3+ times. → auto-route by rule or classifier. - **Repeated status pings / FYIs** — the same kind of update to the same audience on a cadence. → scheduled digest. - **Repeated meeting reschedules** for the same root cause. → auto-propose alternates. - **Repeated RSVPs / tentative responses** to recurring meetings with consistent reasoning. → auto-respond by rule. - **Repeated meeting prep** — gathering the same context before recurring meetings. → pre-meeting brief. - **Repeated doc/wiki updates** — manually appending the same kind of content on a cadence. → scheduled ingest. - **Repeated approvals / sign-offs** of the same class of request. → rule-based pre-screen. - **Repeated file/data shuttling** — move/rename/reformat between systems. → pipeline. - **Repeated drafting** — near-identical emails/messages (welcome notes, onboarding intros, availability, "I have a conflict" replies, follow-ups). → template + auto-fill. **Anti-patterns — do NOT surface** - Normal recurring meeting cadence (standups, weekly syncs) UNLESS there's repetitive *manual* work around them that could be automated. - Anything needing the body of an excluded/private email to reason about. - Automations the user already runs. ## Output List **0–3 candidates max**. If signal is thin (< 3 reinforcing data points across all clusters), output: `✅ No new patterns this run.` Prefer a **mix** — include at least one automation candidate when one qualifies, even if a blog candidate is stronger. Per candidate (≤3 lines each): ``` 💡 **<theme in 5–8 words>** _evidence:_ <1–2 anonymized signals, e.g. "forwarded 4 customer asks to the same engineer this week" or "explained X to 4 different people in chats"> **<blog|automation>** · <1-line rationale. For automation, name the trigger and the action, e.g. "trigger: incoming request → action: auto-route + draft reply".> ``` ## Privacy & guardrails - **Read-only.** Never send any email, chat, channel reply, or Teams message from this skill. Producing the report is the only output. - **Anonymize.** Never include customer/team names, attendee names, meeting times/locations, file paths, or full subjects containing customer identifiers. Say "3 different customers", not the actual names. - **Respect exclusions.** Never open or paraphrase content the user has marked as private or excluded (e.g. performance-review or confidential emails). - When in doubt that a candidate is a real pattern vs. coincidence, drop it — silence is safer than noise.
Colle ce Markdown dans ton agent ou utilise les boutons ci-dessus pour l’écrire dans ton projet.
Ce que fait Pattern Radar (Microsoft)
**Repeated explanation** — the user answers the same question or explains the
**Recurring FAQ** — the same question shows up in 3+ chats/channels from
**Repeated multi-step manual task** — the same sequence of clicks / drafts /
**Repeated handoff / triage** — forwarding, "looping in", or intro'ing the
Comment utiliser Pattern Radar (Microsoft)
1
Copie le prompt
Un clic copie le prompt packagé (ou l'envoie à ton agent).
2
L'agent installe le skill
Il ajoute le SKILL.md et ses ressources à ton projet.
3
Activation automatique
Le skill s'active dès que le contexte correspond.
Déclencheurs pour Pattern Radar (Microsoft)
Dis simplement à ton agent quelque chose comme :
Applique le skill pattern-radar__microsoft-cat-agent-skills__submissions-d8aa62ee163b à cette tâche
Utilise pattern-radar__microsoft-cat-agent-skills__submissions-d8aa62ee163b pour améliorer cette implémentation
Passe en revue ce sujet avec pattern-radar__microsoft-cat-agent-skills__submissions-d8aa62ee163b
Skills liés à Pattern Radar (Microsoft)
Acceleration (Microsoft)
Compare synthetic acceleration options and clearly separate scenario value from forecast commitments.Account Overview (Microsoft)
Create a synthetic Acme account overview and identify evidence that merits seller attention.Acroform Writer (Microsoft)
Use this skill whenever the user wants values written INTO an existing PDF form that lives in the connected SharePoint knowledge source — filling out, completing, populating, or submitting a fillable PDF (application, intake sheet, contract, government form) from data they supply, a spreadsheet row, or the conversation. Triggers include "fill out the job application form", "complete the intake form for [person]", "populate our standard NDA template", and "make this ready to send / non-editable" (flatten). The source form should be found via knowledge search; only ask the user to upload it if knowledge search turns up nothing plausible. different task), and do NOT use it on scanned/image-only PDFs that have no real fillable fields — those need OCR or manual overlay instead, which this skill explicitly detects and reports rather than silently failing.