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 hanamizuki/solopreneur --skill linkedin-growthgit clone --depth 1 https://github.com/hanamizuki/solopreneurWrote 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/hanamizuki/solopreneur/linkedin-growth)<a href="https://agentmods.dev/skills/hanamizuki/solopreneur/linkedin-growth"><img src="https://agentmods.dev/badge/skills/hanamizuki/solopreneur/linkedin-growth/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/hanamizuki/solopreneur/linkedin-growth"><img src="https://agentmods.dev/badge/skills/hanamizuki/solopreneur/linkedin-growth.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 | $0.00140 | $0.03567 |
| Opus 5.5 | $0.00056 | $0.01427 |
| Sonnet 5.5 | $0.00028 | $0.00713 |
| Haiku 4.5 | $0.00014 | $0.00357 |
Grade A, and why
linkedin-growth 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 20d 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 — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Growth Consultant
An interactive skill that helps users grow their LinkedIn presence through evidence-based strategies. Three operating modes, plus a research update mode.
Reference Library
Read the relevant reference file when you need deep knowledge for that topic. Do not load all references at once — pick the one that matches the current conversation stage.
| File | When to read |
|---|---|
references/algorithm.md |
User asks about how LinkedIn works, why reach dropped, or you need to explain the "why" behind a recommendation |
references/profile-optimization.md |
During profile diagnosis or when advising on headline/about/banner/featured |
references/content-strategy.md |
When planning content pillars, post formats, hooks, or templates |
references/engagement-engine.md |
When discussing daily engagement habits, commenting strategy, or connection growth |
references/audience-strategy.md |
When defining target audience, ICP, or the three-audience framework |
references/tools-and-tracking.md |
When setting up KPIs, dashboards, or recommending tools |
references/dm-conversion.md |
When discussing DM strategy, lead conversion, CTA design, buying signals, InMail vs DM, or platform safety limits |
references/case-studies.md |
When user wants proof, examples, or inspiration from real creators |
references/industry-playbooks.md |
When advising users in specific roles (SaaS founder, consultant, job seeker, engineer, recruiter) or when the user is in Taiwan/Asia market |
GTM Integration
Before starting goal setting or plan generation, check if the project has
a completed GTM plan by looking for docs/gtm/gtm-state.yaml:
- If the file exists and
status: complete, read these GTM docs to pre-fill context (brand positioning, target audience, messaging, channels):docs/gtm/01-brand-strategy.md— extract brand voice, positioningdocs/gtm/02-market-landscape.md— extract competitor info, market contextdocs/gtm/03-messaging-framework.md— extract key messages, value propsdocs/gtm/04-channel-playbook.md— check if LinkedIn is already a planned channel
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/algorithm.md 7.5 KB
- references/audience-strategy.md 6.5 KB
- references/case-studies.md 5.3 KB
- references/content-strategy.md 9.9 KB
- references/dm-conversion.md 15 KB
- references/engagement-engine.md 6.6 KB
- references/industry-playbooks.md 27 KB
- references/profile-optimization.md 6.6 KB
- references/tools-and-tracking.md 7.3 KB
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.
- 20d ago First seen · 361 lines · 140 tokens per session scan A 792b948fed5e
linkedin-growth is a skill published in the GitHub repository hanamizuki/solopreneur (154 stars, last pushed 4d ago), licensed MIT. It adds 140 tokens to every session and 3,567 once invoked, about $0.0006 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 2026-09-27.
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