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 skills add matteotitta/genesys-skills --skill content-opsgit clone --depth 1 https://github.com/matteotitta/genesys-skillsWrote 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/skills/matteotitta/genesys-skills/content-ops)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/content-ops"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/content-ops/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/skills/matteotitta/genesys-skills/content-ops"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/content-ops.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 | $0.00110 | $0.01853 |
| Opus 5 | $0.00055 | $0.00927 |
| Sonnet 5 | $0.00022 | $0.00371 |
| Haiku 4.5 | $0.00011 | $0.00185 |
Grade A, and why
content-operations 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 11d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content operations
Take a completed content strategy and operationalize it. Design series arcs, sequence content across channels, build the production pipeline, and optimize per channel. This skill builds the system; downstream skills create individual assets.
When to use
Invoke when user says: "operationalize this content strategy", "content operations / pipeline / calendar for {company}", "serialize our pillars", "how do we produce content at scale?", "set up content production workflow", "content cascade planning", "turn this strategy into a production system".
Do NOT invoke when: building the strategy itself (use content-strategy), creating individual posts (use linkedin-content, youtube-scripts), running a full founder LinkedIn program (use founder-linkedin), auditing existing content (use content-audit).
Inputs
| Input | Required? | Source |
|---|---|---|
| Content strategy (pillars, funnel mix, channels, volume targets, series themes) | Required | content-strategy output |
| TOV guidelines | Recommended | tov-guidelines output |
| Team capacity (people, hours) | Recommended | User |
| Tool stack (Notion, Scripe, Canva, etc.) | Recommended | User |
| Existing calendar, performance data, lead capture setup, CRM details, budget | Optional | User |
Validate before proceeding: strategy with pillars + funnel mapping; channel selection defined; volume targets set; at least one of TOV / team capacity / tool stack. If strategy missing, run content-strategy first. Can proceed with pillars + channels minimum, but flag gaps.
Process
Four phases. Each ends in a checkpoint that gates the next phase. Detailed step-by-step protocols, templates, and tables live in the premium reference.
Phase 1 — Content serialization → the premium reference
Turn strategic pillars into executable multi-part series with narrative arcs.
- Design series arcs per pillar — 1-3 series per pillar, picking arc type (problem / mechanism / case-study / framework / opinion) per the premium reference (series architecture framework).
- Define installment structure — hook escalation, knowledge progression, callback structure, cadence.
- Map funnel-stage formats — assign each series to TOFU / MOFU / BOFU; verify mix matches strategy ratios (typical 40/35/25).
- Create series tracking framework — status, installments published, performance, decision triggers (TWE > 2 → expand; < 0.5 → retire).
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.
- 11d ago First seen · 140 lines · 110 tokens per session scan A e4abf05994b6
content-operations is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 110 tokens to every session and 1,853 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.
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