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 TaplioOfficial/taplio-linkedin-claude-skills --skill linkedin-content-calendar-plannergit clone --depth 1 https://github.com/TaplioOfficial/taplio-linkedin-claude-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/taplioofficial/taplio-linkedin-claude-skills/linkedin-content-calendar-planner)<a href="https://agentmods.dev/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-content-calendar-planner"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-content-calendar-planner/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/taplioofficial/taplio-linkedin-claude-skills/linkedin-content-calendar-planner"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-content-calendar-planner.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 | $0.00116 | $0.02220 |
| Opus 5 | $0.00058 | $0.01110 |
| Sonnet 5 | $0.00023 | $0.00444 |
| Haiku 4.5 | $0.00012 | $0.00222 |
Grade A, and why
linkedin-content-calendar-planner 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 12d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- linkedin-content-calendar-planner — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Content Calendar Planner
The hardest part of LinkedIn is showing up. A calendar makes showing up the easy default.
When to trigger
The user says "plan my month", "give me a content calendar", "I improvise too much", "what should I post next week ?", "build me 4 weeks of content".
Inputs to ask for
- The user's pillars (from the Content Pillars Builder skill).
- The desired posting cadence (3 / 4 / 5 / 7 posts per week). Default to 4. More is rarely better.
- The audience's time zone and the user's best posting windows (default : Tue-Thu 8am-10am local).
- Any specific milestones in the next month (product launch, event, vacation, big news to react to).
- The mix of formats the user is comfortable with (text, carousel, image, poll, video).
Cadence guidance
- Below 3 posts/week : you do not exist. Hard to grow.
- 3 posts/week : minimum to build momentum. Tue-Wed-Thu.
- 4 to 5 posts/week : the growth zone for most creators.
- Daily : only if the user already has a system AND a strong pipeline of ideas. Otherwise it crashes content quality.
Process
- Ask for the inputs above.
- Build the 4-week grid : 1 post per day on the chosen days.
- For each post, pick :
- Pillar (rotating through them so the audience sees the full positioning).
- Format (text / story / listicle / carousel / opinion / poll / image).
- Topic (specific, not generic).
- Hook angle (the type of opening : curiosity, contrarian, number, etc.).
- CTA goal (comment, share, DM, follow, click).
- Front-load the strongest posts in week 1. New systems lose momentum without early wins.
- Leave 1 "wildcard" slot per week to react to news, trends, or live moments.
- Show the grid and get the user to confirm it. The grid is the plan, not the deliverable.
- Once the grid is confirmed, write a complete, publish-ready post for every non-wildcard slot : a real hook, a full body, and a CTA, in the user's voice. Do not stop at a topic line or a brief : the user should be able to read each post end to end. Create each one as a Taplio draft (see the MCP section). Leave wildcard slots as a one-line prompt, not a full draft.
- Keep the whole calendar in memory : the mapping of slot (week, day, date, pillar) to draft id, draft content, and review status (drafted / approved / scheduled). You will need it to walk the user through review and to schedule on approval.
- Review before scheduling. Walk the user through the drafts one at a time (or in batches if they prefer), let them edit any of them, and only schedule a draft once they approve it. Scheduling is the definitive step : nothing gets a date until the user has seen the actual post.
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.
- 12d ago First seen · 123 lines · 116 tokens per session scan A a0b833da8d5c
linkedin-content-calendar-planner is a skill published in the GitHub repository TaplioOfficial/taplio-linkedin-claude-skills (5 stars, last pushed yesterday), licensed MIT. It adds 116 tokens to every session and 2,220 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 2026-08-31.
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