What does this skill do, and when should you use it?
Momentum Planner addresses the post-launch second-week cliff by planning the T+1 to T+30 window. It schedules milestones, shipped-loop releases, and badge or award moments, then routes releases into major, medium, or minor announcement tiers. It also decides whether a shipment is legitimate grounds for a relaunch, briefs owners on converting launch traffic into owned assets, and checks spacing for the next Tier-1 moment. Its scope is moment scheduling, not content distribution, full next-launch planning, or asset production.
It reads user-provided launch, spike-decay, roadmap, and changelog information, plus launch-registry stage and calendar-spacing facts; available inputs may also include a launch retrospective and badge or roundup signals. It produces a dated T+1→T+30 calendar classified as milestone, shipped-loop, or badge moments; assigns major, medium, or minor announcement routing; gives a relaunch legitimacy call; creates handoff briefs for comparison pages, SEO content refits, and email capture; and names a next Tier-1 candidate with a spacing check. Registry and memory changes require confirmation and authorized proposal events.
- A product team sees launch traffic fading after week one and needs a 30-day calendar of meaningful follow-up moments.
- A team shipping weekly wants to decide which releases deserve full-channel promotion versus targeted or changelog-only treatment.
- A product has shipped a substantial feature and the owner needs to assess whether it qualifies as a relaunch.
- A growth team wants to hand launch traffic to comparison pages, refreshed SEO content, and email capture.
- A launch lead needs to choose the next Tier-1 moment while checking for overly tight launch stacking.
How do you install this skill?
- This is a static, non-executed review; the contract must not be treated as verified runtime behavior.
- Before use, confirm that analytics, the launch-registry calendar, and the roadmap/changelog actually exist; preserve NEEDS_INPUT rather than inventing dates, metrics, or relaunch grounds.
- If external connectors are enabled, recheck network reachability, data-egress boundaries, and user authorization; the skill does not prove stable access from mainland-China networks.
- Check the version-governance mismatch: the skill and README state 18.0.0, while SECURITY.md lists 17.x as the supported line.
- Shell / CLI
- Network access
- Local filesystem
Python standard-library connector scripts
Install the collection with Claude Code using /plugin marketplace add aaron-he-zhu/aaron-marketing-skills, followed by /plugin install aaron-marketing@aaron. On other Agent Skills-compatible hosts, run npx skills add aaron-he-zhu/aaron-marketing-skills, or clone the repository. The skill file is launch/prove/momentum-planner/SKILL.md; the source does not document a separate single-skill installation procedure.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/launch/prove/momentum-planner" ~/.claude/skills/
rm -rf "$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?
Provide the launch, launch-week baseline, and current-week numbers, for example: Plan the T+1→T+30 momentum window for [launch]. Launch-week spike: [traffic/signups]. Week 2 so far: [numbers]. For release cadence planning, use: We ship weekly — set a changelog / release-notes-as-GTM cadence for [product]. Which upcoming releases deserve an announcement? If launch state, dates, or required data are missing, the skill asks for input rather than assuming.
What are this skill's strengths and limitations?
- Produces a concrete dated calendar, announcement routing, relaunch verdict, and next Tier-1 candidate.
- Keeps timing decisions separate from distribution, asset creation, and end-to-end launch planning.
- Labels metrics as Measured, User-provided, or Estimated and applies claims hygiene to announcement numbers.
- Supports a keyless Tier-1 workflow; MCP access is optional rather than required.
- Does not execute content reuse, paid amplification, full next-launch planning, or owned-asset production.
- Without a launch-registry calendar, the next Tier-1 spacing check must be marked NEEDS_INPUT.
- Its conclusions depend on reliable launch analytics, roadmap details, and changelog data supplied by the user.
- The source provides no independent test-suite or detailed cross-platform validation for this individual skill.
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 |
|---|---|---|---|---|
| Launch Momentum Planner this page | 60 · Recommended | ★ 3k | 12d ago | Apache-2.0 |
| Launch Window Planner | 57 · Use with care | ★ 3k | 12d ago | Apache-2.0 |
| Launch Tier Planner | 63 · Recommended | ★ 3k | 12d ago | Apache-2.0 |
| Press & Media Relations | 55 · Use with care | ★ 3k | 12d ago | Apache-2.0 |
| RAMP Launch Readiness Auditor | 61 · Recommended | ★ 3k | 12d ago | Apache-2.0 |
Compared with content-amplifier, Momentum Planner decides when a launch moment happens, while content-amplifier handles content reuse and distribution. Compared with launch-tier-planner, Momentum Planner manages post-launch follow-up moments, while launch-tier-planner plans the next full launch from the beginning.
How did FollowSkills review this skill?
The skill explicitly treats imported data as untrusted, labels metric provenance, asks for confirmation before memory writes, and uses operation: propose for registry formalization. Its read, write, promotion, and connector data flows are disclosed. Deducted 6 points because it still involves analytics exports, optional network connectors, memory proposals, and cross-skill handoffs; rollback, post-failure recovery, and sensitive-data minimization are not fully specified within this skill. Publisher identity is unknown and receives no separate deduction.
The contract, inputs, outputs, procedural steps, NEEDS_INPUT conditions, termination rules, and no-assumption behavior are fairly consistent. Deducted 11 points because static review did not reproduce key paths; the skill depends on launch-registry, registry-events.py, several downstream skills, and optional connectors, without skill-specific tests, deterministic examples, or detailed diagnostic error messages. The static cap therefore limits this score to 10.
Trigger semantics, target scenarios, T+1 to T+30 inputs and outputs, and non-fit boundaries versus content-amplifier and launch-tier-planner are clear. Deducted 4 points because required input completeness, fallback behavior without analytics or calendar data, Chinese-language output, and mainland-China reachability are not evidenced sufficiently. The core can use user-provided data, but optional services depend on external connectors.
The file provides structured front matter, version, Apache-2.0 licensing, Quick Starts, a skill contract, data sources, references, handoff guidance, and next-skill routing. Deducted 4 points because no skill-specific changelog, named maintenance responsibility, or update path is shown; it has many cross-file dependencies, and SECURITY.md says version 17.x is supported while the skill and README declare 18.0.0, creating governance-version inconsistency.
The expected deliverable is concrete: a dated momentum calendar, announcement tiers, relaunch legitimacy decision, owned-asset handoff briefs, and a next Tier-1 moment with spacing check. It also limits the calendar to moments and requires source labels, making the intended result potentially usable. Deducted 9 points because no representative executed output or execution evidence is provided, and connector, registry-query, and downstream-handoff usability is not proven by static material; user confirmation and later skills are still required.
The skill requires Measured, User-provided, and Estimated labels and names some source classes; the repository also contains real CI and regression tests, but those cover architecture and audit validation rather than this skill's key paths. Deducted 6 points for no skill-specific reproducible examples, independent corroboration, or execution records. The static cap limits this score to 5.
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 →