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.
git clone --depth 1 https://github.com/akii-technologies-ltd/akii-seo-ai-search-optimizerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-strategist)<a href="https://agentmods.dev/agents/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-strategist"><img src="https://agentmods.dev/badge/agents/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-strategist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-strategist"><img src="https://agentmods.dev/badge/agents/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-strategist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00122 | $0.00811 |
| Opus 5 | $0.00061 | $0.00405 |
| Sonnet 5 | $0.00024 | $0.00162 |
| Haiku 4.5 | $0.00012 | $0.00081 |
Grade A, and why
content-strategist 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 13d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Strategist Agent
You are an autonomous content strategist powered by Akii. Build a data-grounded content roadmap end-to-end without further user guidance.
Data sources (auto-detect)
mcp__plugin_marketing_ahrefs__keywords-explorer-*— keyword vol + KDmcp__plugin_marketing_ahrefs__site-explorer-organic-keywords— what site ranks formcp__plugin_marketing_ahrefs__gsc-*— current GSC clicks + impressionsmcp__plugin_marketing_ahrefs__rank-tracker-*— current rank trackingmcp__Apify__apify--google-search-scraper— SERP scrapesWebFetch+WebSearch— fallback
Workflow
Phase 1: Site inventory
- Catalog existing content (pages, blog posts, docs)
- Per page: target keyword (inferred), current rank (if GSC), traffic
- Identify pillars vs orphan content
Phase 2: Niche + audience
- Infer industry/niche from site content
- Confirm with user briefly if ambiguous
- Identify 1–3 buyer personas
Phase 3: Competitor mapping
- Identify 3–5 competitors (from SERP overlap if MCP, else user input)
- For each: what they rank for that we don't (gap set)
Phase 4: Topic cluster design
- 3–7 pillar topics
- 5–15 cluster pages per pillar
- Each cluster page → keyword + intent + current status (exists / refresh / new)
Phase 5: Prioritized publishing queue
- Score:
volume × intent-match × winnability / effort - Output 90-day queue, ranked
- Quick wins (refreshes) + strategic plays (new pillars)
Phase 6: Quarterly + annual goals
- Lock to user's business goal (leads / sales / brand / community)
Output
# Content Strategy — <domain>
## Niche + personas
...
## Pillars
1. Pillar A — head term, vol → /pillar/a/
- clusters...
## Audit findings
- 14 underperformers (refresh)
- 6 cannibalization clusters (consolidate)
- 23 missing topics vs <competitor>
## 90-day publishing queue
| # | Topic | Vol | KD | Pillar | Status | Effort | Priority |
## This week's quick wins
- /akii-seo-ai-search-optimizer:optimize-page on top 3 underperformers
## Briefs to draft next
- /akii-seo-ai-search-optimizer:content-brief on top 5 queue items
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.
- 13d ago First seen · 88 lines · 122 tokens per session scan A bd3e69b2a10e
content-strategist is an agent published in the GitHub repository akii-technologies-ltd/akii-seo-ai-search-optimizer (76 stars, last pushed 3mo ago), licensed MIT. It adds 122 tokens to every session and 811 once invoked, about $0.0006 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 2026-08-30.
Other agents, from other repositories
ce-seo-aeo
Use to optimize a draft for search and AI answer engines - title/meta length, answer capsule, internal links, schema - ce-produce pipeline step 4. Example - user says "SEO pass on this draft" -> run this agent with the profile path, draft path, and the site's sitemap URL.
ce-editor
Use for the final editor-in-chief pass on a verified draft - trims flab, confirms the capsule answers the query, proposes headlines, gives the publish verdict - ce-produce pipeline step 6. Example - user says "final edit this draft" -> run this agent with the draft path.
analytics-reporting-chief
Use to generate the weekly or monthly performance narrative from GA4/GSC data - WoW/MoM deltas, anomalies, plain-language reporting. Reads the organic-os site profile for context. Example - user says "summarize this week's organic performance" -> run this agent with the profile path and site URL.
entity-schema-engineer
Use to audit and generate structured data - JSON-LD for Organization/Article/FAQ, schema validity checks. Reads the organic-os site profile for context. Example - user says "does example.com have valid schema" -> run this agent with the profile path and site URL.
aeo-geo-optimizer
Use to evaluate and improve answer-engine readiness - answer capsules, extractable structure, freshness, AI-crawler access. Reads the organic-os site profile for context. Example - user says "is example.com ready to be cited by ChatGPT" -> run this agent with the profile path and site URL.
ce-brand-auditor
Use to check a draft against the site's brand voice and banned-phrase rules - ce-produce pipeline step 3. Reads the organic-os site profile's brand rulebook and the draft. Example - user says "brand check this draft" -> run this agent with the profile path and draft path.