What does this skill do, and when should you use it?
This skill plans the pre-promotion ramp for selected communities. For each community, it defines account-history expectations, a give-before-ask ledger, dated etiquette and rule notes, a human-run participation cadence, and testable warming-to-active graduation criteria. It also covers entry paths and member lifecycles for owned Discord, Slack, forum, or enterprise WeChat spaces. It does not run launch-day submissions or automated engagement; it hands the evidence to channel-registry.
Reads the selected channel set, phased-entry handoff, existing account standing, public community rules, and user-provided material for closed platforms. It uses public community surfaces and the repository's named connectors where applicable. It labels account-history expectations as Estimated with named sources, records Measured, User-provided, or Estimated values, and produces per-community rule digests, ledger specifications, weekly human participation cadences, and graduation criteria. It submits graduation criteria, cadence commitments, and channel-state evidence as proposal events to memory/events/channels.ndjson and emits the standard handoff summary.
- A marketing team preparing to promote a beta in Reddit, Hacker News, or a niche Discourse forum over several weeks.
- A team with an existing Xiaohongshu account that needs a warming-to-active checklist based on exported account evidence.
- A team opening a Discord, Slack, forum, or enterprise WeChat community that needs entry incentives and lifecycle stages.
- A multi-community campaign team that must identify rule conflicts instead of using one uniform promotion push.
How do you install this skill?
- Do not treat Estimated account thresholds or give:ask ratios as platform rules; verify each community’s current rules and source date.
- Redact account screenshots, exports, and private-community member data and define retention before processing; memory writes still require user confirmation.
- For mainland-China platforms, rules and account standing depend on user-provided material, so this skill alone cannot ensure timeliness, reachability, or compliance.
- Before adoption, resolve the 18.0.0 versus SECURITY.md 17.x support-line inconsistency and confirm that all referenced files and connectors exist.
- Shell / CLI
- Network access
- Local filesystem
Python standard library
The repository README supports Claude Code installation with /plugin marketplace add aaron-he-zhu/aaron-marketing-skills, followed by /plugin install aaron-marketing@aaron. Agent Skills-compatible hosts can use npx skills add aaron-he-zhu/aaron-marketing-skills, or the repository can be cloned with git clone https://github.com/aaron-he-zhu/aaron-marketing-skills. The README documents the single-skill command pattern but does not provide this skill's exact CLI selector example. The repository is licensed under Apache-2.0.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/social/explore/participation-warmup-planner" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
After installation, provide the community list, promotion window, and existing account standing. Example: Plan the participation warmup for r/selfhosted, Hacker News, and our niche Discourse forum — we want to promote the beta in 8 weeks. If no community list is available, the skill stops with NEEDS_INPUT and routes to channel-portfolio-planner. After delivery, it hands the plan to channel-registry and asks whether to save the results.
What are this skill's strengths and limitations?
- Produces concrete per-community outputs: rule digest, account expectations, give-before-ask ledger, cadence, and graduation evidence.
- Requires Measured, User-provided, or Estimated labels and named sources for Estimated thresholds.
- Explicitly prohibits karma farming, engagement pods, scripted replies, bulk DMs, and automated participation.
- Supports both public communities and owned Discord, Slack, forum, and enterprise WeChat spaces.
- Does not choose the channel portfolio or execute launch-day submissions, posts, replies, or DMs.
- Closed-platform rules and account standing depend on user-provided pastes, exports, or screenshots.
- Public-source retrieval and registry event submission require network and local filesystem access.
- The README version badge says 18.0.0 while the skill frontmatter says 19.0.0, indicating version metadata is not fully synchronized.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Community Participation Warmup Planner this page | 57 · Use with care | ★ 3k | 12d ago | Apache-2.0 |
| Social Measurement Loop | 56 · Use with care | ★ 3k | 12d ago | Apache-2.0 |
| Social Selling Planner | 60 · Recommended | ★ 3k | 12d ago | Apache-2.0 |
| Channel Portfolio Planner | 57 · Use with care | ★ 3k | 12d ago | Apache-2.0 |
| Platform Norm Profiler | 60 · Recommended | ★ 3k | 12d ago | Apache-2.0 |
This skill sits alongside the repository's channel-portfolio-planner, channel-registry, and community-launch-runner: the first selects channels, this skill plans the warmup, channel-registry records state, and community-launch-runner handles launch-day submissions. It is not a replacement for those skills.
How did FollowSkills review this skill?
The skill explicitly requires human execution and prohibits karma farming, scripted replies, bulk DMs, and reciprocal engagement. It treats rules and exports as untrusted, asks before memory writes, and limits registry changes to proposal events, showing strong permission boundaries. Seven points are deducted because account history, screenshots, and analytics exports may contain sensitive data without explicit minimization, redaction, retention, or deletion rules; connector data flows and recovery boundaries are mostly delegated to repository-wide documents rather than specified here.
Inputs, outputs, scope boundaries, termination conditions, and the NEEDS_INPUT path are comparatively clear, with distinctions between public and closed platforms. Eleven points are deducted because key connectors, registry behavior, and upstream skills referenced by the path are not fully supplied here, and no path-specific tests or reproducible execution records are shown. Diagnostics for malformed platform data, missing rules, and connector failures remain thin. The static ceiling of 10 is applied.
Triggers, scenarios, non-fit boundaries, inputs, outputs, and the owned-community variant are clearly described, including Chinese-platform use cases. Four points are deducted because geo-relevance is declared low; core data for mainland-China platforms depends on user-pasted rules, exports, or screenshots, while platform coverage and exclusion conditions still require manual judgment. Reachability and consistent fit in the target environment are not demonstrated.
The skill provides version 18.0.0, an Apache-2.0 license, Quick Starts, a structured contract, data sources, save rules, references, next-skill routing, and termination rules. Five points are deducted because maintenance ownership, update path, and changelog evidence are not clear in the supplied material; SECURITY.md still identifies 17.x as the supported current line while the skill and README state 18.0.0; and extensive cross-file references create hidden installation and troubleshooting assumptions.
The contract defines a per-community rule digest, account-history expectations, a give-before-ask ledger, human cadence, graduation criteria, and handoff, which could produce a directly useful warming plan. Nine points are deducted because this review is static and supplies no representative artifact or third-party execution evidence; the standard handoff format and some critical reference templates are only linked, so practical output may require substantial manual completion. The static ceiling of 7 is applied.
Requiring Estimated labels with named sources, URLs and last-verified dates for rules, and third-party-checkable graduation criteria improves auditability. Seven points are deducted because the supplied material contains no actual community rules, source examples, sample generated plan, or independent reproduction. Repository tests mainly cover architecture and audit-artifact validation, not this skill’s factual correctness or key paths. The static ceiling of 5 is applied.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →