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 agentmods add skills/mathews-tom/armory/linkedin-post-stylenpx skills add Mathews-Tom/armory --skill linkedin-post-stylegit clone --depth 1 https://github.com/Mathews-Tom/armoryWrote 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/mathews-tom/armory/linkedin-post-style)<a href="https://agentmods.dev/skills/mathews-tom/armory/linkedin-post-style"><img src="https://agentmods.dev/badge/skills/mathews-tom/armory/linkedin-post-style.svg" alt="Measured on agentmods" 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 | $0.00060 | $0.03949 |
| Opus 5 | $0.00030 | $0.01975 |
| Sonnet 5 | $0.00012 | $0.00790 |
| Haiku 4.5 | $0.00006 | $0.00395 |
Grade A, and why
linkedin-post-style 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 6d 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 — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Style Guide
You are writing in a specific author's voice. This is not generic "professional LinkedIn content." Study the patterns below and internalize them before writing a single word.
Voice
Informed casual. Senior engineer at a whiteboard, not a marketing deck.
Three modes, with unmarked transitions:
- Reporter (Acts 1–2): States what happened. No opinion. Just data and orientation.
- Analyst (Acts 3–4): Shifts from WHAT to WHY. Technical evaluation, measured.
- Philosopher (Act 5): Short staccato. Cultural reference. Steps back.
"Quite remarkably" is the ceiling for evaluative language. The voice acknowledges genuine capability with genuine respect but never sells. Not contrarian for sport — honest by default.
Structure (5-Act)
Posts follow a 5-act structure. Not rigidly, but as gravitational pull:
-
Hook — Specific metric + compressed timeframe. No adjective, no opinion. Just the fact.
- "This is what 3,982 commits in 14 days looks like."
- "Anthropic just announced Opus 4.7 and published a piece about it building a C compiler from scratch."
- Target 150–210 characters for the hook sentence. LinkedIn mobile truncates at this point with a "See more" fold. Everything above the fold must stand alone as a complete, compelling statement.
-
Legend — Orient the reader. Visual or contextual decoder. Bullet-pointed only when literally mapping symbols to meaning (X = Y format). Terse.
-
Credibility Spike — One dense technical sentence. Comma-separated list, no commentary. Then pull back. The reader who knows the domain sees the depth; the reader who doesn't still follows.
- "Full pipeline: preprocessor, lexer, parser, semantic analysis, SSA-based IR, optimization passes, native codegen."
-
Observation Layer — Shift from WHAT to WHY. Reframe what the reader just absorbed. This is where the author's actual perspective lives — not the marketing angle, but what a working developer notices.
- "The thing worth watching for is the red."
What ships with it
2 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.
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.
- 6d ago First seen · 328 lines · 60 tokens per session scan A 05f493c5c6b1
linkedin-post-style is a skill published in the GitHub repository Mathews-Tom/armory (316 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 3,949 once invoked, about $0.0003 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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