Install
$ agentstack add skill-social-media-skills-skills-engagement-routine ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Engagement Routine
The operating system for engagement. reply-and-comment-writer is the craft (what to say); this is the cadence (when, how much, in what order, sustainably). The growth skills all call for "an engagement routine" — this is it.
The data is blunt: replying is the highest-return activity on every platform, the first ~15–20 minutes after posting matter most, and comments/DMs outweigh likes. But it only works as a habit — and the habit only survives if it's sustainable (≈46% of social pros have considered quitting over stress). So this skill optimizes for **return and longevity.**
Step 0 — Read the context
Load brand-profile.md / social-strategy.md: who the ICP is, which platforms actually matter, and how much time the user realistically has. Right-size everything to that.
Step 1 — Set the cadence (windows, not all-day)
Design time-boxed engagement windows instead of all-day grazing — e.g. ~20 min morning + ~20 min afternoon, plus a golden-hour pass right after each post publishes. Order within each window: comments → DMs → urgent/negative → proactive comments on ICP/peers/leaders. See references/the-daily-and-weekly-routine.md.
Step 2 — Free the time (the flywheel)
"No time to engage" is solved by batching + scheduling content (→ batch-content-plan, scheduling-and-queue) to reclaim the hours, then spending them engaging. The flywheel: schedule → freed time → genuine engagement → reach/relationships → more reach. Time posts for windows you can be present. See references/the-scheduling-engagement-flywheel.md.
Step 3 — Triage & aim at a goal
When time is short, do the highest-return things first (golden-hour comments → DMs → negative → proactive), focus on the right people (ICP/peers), not vanity volume, and map the routine to a goal with 2–3 meaningful signals you can read natively (no WoopSocial analytics). See references/triage-priorities-and-goals.md.
Step 4 — Make it sustainable
Build in boundaries: notification discipline, set + communicate response windows, protect off-hours, and prefer a small repeatable routine you keep over a heroic one you abandon. Consistency at a holdable pace beats sprints. See references/sustainability-and-boundaries.md.
How it runs (advisory + honest)
- WoopSocial has no inbox/analytics. It publishes/schedules (the flywheel's first half); it
cannot pull comments/DMs, post replies, or report performance. The human engages in-app via native notifications; the agent drafts replies/comments (→ reply-and-comment-writer).
- Genuine only. No automation, bots, mass auto-comments, or bought/fake engagement — detected,
penalized, self-defeating. The agent assists by drafting; the human does the real interacting.
Quality bar — self-check
- Did I design a concrete, time-boxed daily + weekly cadence, centered on the golden hour?
- Did I use the flywheel (schedule to free the time) and right-size to the user's time/platforms?
- Did I give a triage order, aim at a goal with native signals (no fabricated analytics), and
focus on the right people?
- Did I make it sustainable (boundaries, response windows, not always-on)?
- Did I keep it advisory (human engages in-app, agent drafts) and genuine (no automation/fake)?
Edge cases & pushback
- "Auto-reply / mass-comment for me" → refuse automation/fake; genuine routine + draft-for-review.
- "WoopSocial: pull my comments + tell me the best time" → no inbox, no analytics; native inbox +
agent drafts.
- "No time to engage" → batch + schedule to free time (the flywheel); don't engage less.
- "Reply to everyone everywhere" → triage + the right people; done beats perfect.
- "I'm burning out checking all day" → windows + notification discipline + response boundaries.
- "How do I know it's working?" → goal + native signals (comment depth, DM convos); no vanity, no
fabricated numbers.
Related
reply-and-comment-writer— the craft this schedules (drafts the replies/comments/DMs).scheduling-and-queue,batch-content-plan— the flywheel's first half (free the time).instagram-growth,tiktok-growth,linkedin-growth— call for this routine; strategic commenting.community-management— deeper community;crisis-and-moderation— real crises;social-strategy— the goals.
References
references/the-daily-and-weekly-routine.md— the concrete cadence: windows, the golden hour, order of operations, weekly rhythm, scaling.references/the-scheduling-engagement-flywheel.md— freeing time by scheduling, the flywheel, and the honest WoopSocial boundary.references/triage-priorities-and-goals.md— what to do first, the right people, and goal/signals without analytics.references/sustainability-and-boundaries.md— anti-burnout boundaries, consistency at a holdable pace, genuine-only.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: social-media-skills
- Source: social-media-skills/skills
- License: MIT
- Homepage: https://social-media-skills.com
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.