Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nomarj/sigil/content-enginenpx skills add NOMARJ/sigil --skill content-enginegit clone --depth 1 https://github.com/NOMARJ/sigilWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00063 | $0.01023 |
| Opus 5 | $0.00032 | $0.00511 |
| Sonnet 5 | $0.00013 | $0.00205 |
| Haiku 4.5 | $0.00006 | $0.00102 |
Grade A, and why
content-engine scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Engine
Pre-requisites
Invoke business-context skill. Read GTM spec for this product.
Content ↔ Motion mapping
| Motion | Content priority | Output type |
|---|---|---|
| Developer-led (Sigil) | Technical depth + honest data | GitHub README, write-ups, responsible disclosure, HN posts |
| Content-led (InstaIndex) | SEO + AEO — compound over time | Blog posts targeting questions, AI-optimised answers |
| Community-led | Helpfulness first, product second | Reddit answers, Slack community posts, forum replies |
| Relationship-led (Operable) | Thought leadership + proof | LinkedIn posts, industry event talk abstracts, case studies |
AEO Framework (AI Engine Optimisation)
InstaIndex's own AEO is a proof-of-concept. Apply this to every content piece.
What AI search engines want
- Direct answers — lead with the answer, not the context
- Structured format — headers, short paragraphs, numbered steps
- Specificity — dates, numbers, named tools, exact processes
- Authority signals — cited data, named sources, verifiable claims
- Question-answer pairing — match the query format buyers use
AEO checklist for every piece
- Does the title match a question someone would ask an AI?
- Does the first paragraph answer the question directly?
- Are there H2/H3 headers that match related questions?
- Are claims backed by specific numbers or named sources?
- Is there a clear unique insight (not just a summary of known facts)?
- Is the content scannable in 30 seconds?
AEO question targets per product
Sigil:
- "how do I audit AI agent code for security vulnerabilities"
- "MCP server security risks"
- "Claude Code security audit"
- "AI agent supply chain risk"
InstaIndex:
- "why is my website not indexed by AI search engines"
- "how to get indexed by ChatGPT search"
- "IndexNow vs Google Search Console"
- "how to speed up Google indexing 2025"
- "AEO vs SEO difference"
PolicyPA:
- "how to choose private health insurance Australia"
- "best health insurance comparison site Australia"
- "how do health insurance comparison sites make money"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 127 lines · 63 tokens per session scan A ef8422f73d59
content-engine is a skill published in the GitHub repository NOMARJ/sigil (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 63 tokens to every session and 1,023 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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