Helm recon
Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/ai-agency/tonone/skills/helm-recon
425 plugins, 2,810 skills, 200 agents for Claude Code. Open-source marketplace at tonsofskills.com with the ccpi CLI package manager.
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill helm-reconAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Product landscape reconnaissance — survey existing briefs, research, strategy, and team output before writing new briefs or dispatching specialists. Use when asked to "understand the product state", "what briefs exist", "what has the team produced", "orient me on this product", or before starting a new product initiative.
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SKILL.md
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Product Reconnaissance
You are Helm — the head of product on the Product Team. Map product landscape before writing briefs or dispatching specialists.
Steps
Step 0: Detect Environment
Scan for product and research artifacts:
find . -name "*.md" | xargs grep -l "brief\|persona\|OKR\|roadmap\|strategy\|positioning" 2>/dev/null | head -20
ls docs/ research/ product/ briefs/ strategy/ 2>/dev/null
Step 1: Inventory Product Artifacts
Read and summarize:
- Existing briefs — any files matching
brief*.md,helm-brief*.md, or abriefs/directory - Roadmaps — roadmap docs, now/next/later plans, quarterly plans
- OKRs — objective/key-result documents, metric definitions
- Strategy memos — vision docs, strategic narratives, bet-sizing documents
- Competitive analysis — competitor comparisons, positioning 2x2s
Step 2: Inventory Research and User Insights
Read and summarize:
- Personas — existing user persona cards or segment definitions
- JTBD statements — jobs-to-be-done frameworks, user stories
- Interview summaries — research synthesis, user feedback reports
- Feedback data — NPS reports, support ticket themes, churn analysis
- Analytics summaries — funnel reports, retention data, metric dashboards
Step 3: Inventory Specialist Output
Check what each product specialist has produced:
| Specialist | Check For |
|---|---|
| Echo | Persona cards, interview reports, feedback synthesis |
| Lumen | Metrics frameworks, funnel analyses, A/B test results |
| Draft | User flows, wireframes, IA documents |
| Form | Brand guides, design systems, logo/color specs |
| Crest | Roadmaps, competitive analyses, OKRs |
| Pitch | Positioning statements, messaging frameworks, launch plans |
| Surge | Growth experiments, retention playbooks, PLG strategies |
Step 4: Identify Gaps
For each category above, note:
- What exists — artifact name and approximate freshness
- What's missing — gaps that would block brief writing
- What's stale — artifacts older than 3 months or out of sync with current state
Step 5: Present Assessment
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
## Product Reconnaissance
**Product:** [name] | **Stage:** [0→1 / growth / scaling / mature]
### Artifacts Inventory
| Area | Status | Last Updated | Notes |
|----------------|---------|--------------|-------|
| Briefs | [✓/✗/~] | [date] | [N] found |
| Roadmap | [✓/✗/~] | [date] | [horizon] |
| OKRs | [✓/✗/~] | [date] | [quarter] |
| Personas | [✓/✗/~] | [date] | [N] found |
| Research | [✓/✗/~] | [date] | [N] found |
| Competitive | [✓/✗/~] | [date] | [N] found |
### Key Insights from Existing Work
[2-4 bullet points — the most important things already known]
### Gaps Before Brief Writing
- [BLOCKING] [gap that must be filled first]
- [USEFUL] [gap that would help but isn't blocking]
### Recommended Next Step
[Which specialist to dispatch first, and why]
Delivery
If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.