Install
$ agentstack add skill-cgallic-kai-cmo-harness-content-ideas ✓ 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.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
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
/content-ideas — The Research Lead
"What should I write next?" This skill analyzes your GSC keyword data to find high-potential topics — keywords you already rank for that could perform better with targeted content.
Arguments
Optional:
- site: Site key to analyze (required if multiple sites configured)
- --count: Number of ideas to suggest (default: 10)
Example: /content-ideas kaicalls Example: /content-ideas kaicalls --count 5
The Skill
Step 1: Pull GSC Keyword Data
Run:
kai-report --site {site} --format json
Also pull keyword opportunities by looking for:
- Keywords at position 5-20 (striking distance — could reach page 1 with targeted content)
- Keywords with high impressions but low CTR (opportunity for better content)
- Keywords with high CTR but low impressions (opportunity for broader targeting)
Step 2: Cross-Reference with Personas
For each keyword opportunity, match it against the 8 personas in knowledge/personas/. Score each keyword-persona match by relevance.
Step 3: Score and Rank
Calculate an Opportunity Score (0-100) for each keyword based on:
- Position gap: How close to page 1? (position 5-10 = high, 10-20 = medium, 20+ = low)
- Impression volume: Higher impressions = bigger opportunity
- CTR gap: Current CTR vs expected CTR for that position = room for improvement
- Persona match: Strong persona match = higher score
- Existing content: Already have content targeting this? Lower score (avoid cannibalization)
Step 4: Display Ideas
CONTENT IDEAS — {site}
══════════════════════════════════════════
Top {N} topics ranked by opportunity score:
#1 [92] "AI receptionist for law firms"
Position: 8 | Impressions: 1,240/mo | CTR: 1.8%
Persona: Shock Absorber
Why: Position 8 with high impressions — one quality blog post could reach page 1
Format: blog (recommended)
#2 [85] "virtual receptionist vs answering service"
Position: 12 | Impressions: 890/mo | CTR: 0.9%
Persona: System Manager
Why: Comparison keyword — no existing content targeting this directly
Format: blog (recommended)
#3 [78] "law firm after hours answering"
Position: 15 | Impressions: 2,100/mo | CTR: 0.4%
Persona: Shock Absorber
Why: High impression volume at position 15 — significant traffic upside
Format: seo (recommended)
...
Step 5: Offer Next Step
"Want to create a brief for any of these? Type /content-brief {format} {site} \"{keyword}\" to start."
If user picks one, suggest the exact command.
Error Handling
- No GSC data: "GSC data unavailable. Configure your site's GSC property in
kai-config set sites.{site}.gsc_property {value}" - No existing content: "No published content for {site}. Ideas are based on GSC data only — publish your first piece with
/marketing-sprintto start the feedback loop."
Chain State
Standalone: First skill in a new content cycle Feeds into: /content-brief (user picks a topic)
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: cgallic
- Source: cgallic/kai-cmo-harness
- License: MIT
- Homepage: https://meetkai.xyz
Install and usage instructions live in the source repository linked above.
Reviews
No reviews yet, be the first.
Write a review
Versions
- v0.1.0 Imported from the upstream source.