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 styfinity/linkedin-engine --skill linkedin-content-calendargit clone --depth 1 https://github.com/styfinity/linkedin-engineWrote 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/styfinity/linkedin-engine/linkedin-content-calendar)<a href="https://agentmods.dev/skills/styfinity/linkedin-engine/linkedin-content-calendar"><img src="https://agentmods.dev/badge/skills/styfinity/linkedin-engine/linkedin-content-calendar/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/styfinity/linkedin-engine/linkedin-content-calendar"><img src="https://agentmods.dev/badge/skills/styfinity/linkedin-engine/linkedin-content-calendar.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 | $0.00039 | $0.00457 |
| Opus 5.5 | $0.00016 | $0.00183 |
| Sonnet 5.5 | $0.00008 | $0.00091 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
linkedin-content-calendar 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 2mo 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.
What it actually says
LinkedIn Content Calendar
One week, five posts, five lanes. This skill sets the slate so every post proves a competence the buyer actually pays for, with enough variety that the feed never feels like the same post twice.
Inputs
- The week's theme or the proof on hand, plus which lane needs weight: $ARGUMENTS
- The brief (lanes, voice profile, offer, pains, and what has run recently) loads automatically.
Do this
- Assign one post to each of the five revenue lanes: Get Found, Get Chosen, Get the Meeting, Close the Deal, Operating System.
- Apply the locked variety mix across the five, one type each: a deep operator-playbook post, an ultra-short screenshot-and-share, a second deep post, a proof / business-case post, a punchy mid-length opinion.
- Pick five DIFFERENT hook formulas, one per post. No formula repeats inside the week.
- Check the last six weeks. Do not repeat a framework angle that has run in that window. If the theme forces a repeat, rotate the angle or swap the proof.
- For each post, set the comment keyword (one word, easy to type, tied to the lane's lead magnet or follow-up).
Output
A five-row table with columns: Day, Type, Lane, Hook formula, Angle (one line), Keyword. Then one line naming the through-line that ties the five posts into a single week.
Rules
- Every post must prove a competence the buyer buys. If a post only entertains, cut it and reassign the lane.
- No angle and no hook formula repeated inside the week; no framework angle repeated inside six weeks.
- This skill plans only. It does not write the posts. Hand each row to the drafting skills, then run /linkedin-humanizer on the drafts before anything is scheduled.
- No em-dashes.
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.
- 2mo ago First seen · 30 lines · 39 tokens per session scan A eae17a8595ed
linkedin-content-calendar is a skill published in the GitHub repository styfinity/linkedin-engine (9 stars, last pushed 4mo ago), licensed MIT. It adds 39 tokens to every session and 457 once invoked, about $0.0002 per session on Opus 5.5. 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.
linkedin-content-calendar compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| linkedin-content-calendarstyfinity/linkedin-engine | Skill | 9 | 4mo ago | MIT | A | 39 | Claude Code |
| LinkedIn Automationclaude-office-skills/skills | Skill | 567 | 9mo ago | MIT | A | 19 | Claude Code, Codex |
| linkedin-carouselsericrisco/rsc-harness | Skill | 529 | 4d ago | MIT | A | 91 | Claude Code, Codex |
| deepline-ads-audiencesgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 133 | Claude Code, Codex |
| deepline-analyticsgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 115 | Claude Code |
| deepline-enginegetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 43 | Claude Code, Codex |
| deepline-gtmgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 332 | Claude Code, Codex |