Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add nicknisi/claude-plugins/plugin install contentWrote 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/nicknisi/claude-plugins/blog-post-writer)<a href="https://agentmods.dev/skills/nicknisi/claude-plugins/blog-post-writer"><img src="https://agentmods.dev/badge/skills/nicknisi/claude-plugins/blog-post-writer/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/nicknisi/claude-plugins/blog-post-writer"><img src="https://agentmods.dev/badge/skills/nicknisi/claude-plugins/blog-post-writer.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 | $0.00078 | $0.01632 |
| Opus 5 | $0.00039 | $0.00816 |
| Sonnet 5 | $0.00016 | $0.00326 |
| Haiku 4.5 | $0.00008 | $0.00163 |
Grade A, and why
blog-post-writer 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 10d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nick Nisi Blog Writer
Turn raw material into a draft Nick finishes. This skill does research, structure, and connective prose. It does not produce publishable first-person writing.
The rule this skill exists to enforce
Facts may come from logs. Feelings may not.
An earlier version of this skill shipped a post that readers called AI slop. The facts were impeccable — real timestamps, real commit stats, real Slack quotes. The failure was that it also generated Nick's inner life: what he thought, what he'd assumed, what moved him. Nine such claims; one had a source. Readers can't always name that, but they feel it, and they stop trusting the piece.
The measured version: that post claimed inner states at 5.84 per 1,000 words against Nick's corpus mean of 0.97. Six times his rate. He mostly writes about what he built. The draft wrote about how he felt about what he built.
Everything below follows from that.
Process
1. Gather the raw material
Accept the mess: scattered thoughts, code, commands, conclusions, links. Don't require organization.
If the material is thin, mine it — session logs, Slack, git history, the repos themselves. This is the pipeline's genuine strength and there's no reason to hold back. Record a source for every fact. A working file of claim → source keeps the draft honest and makes step 5 mechanical.
2. Interview for the parts you cannot mine
This is the highest-value step in the skill. Do not skip it.
Logs record what Nick did. They never record what he thought. Ask 8–15 targeted
questions with ask_user_question or plain prose, and capture the answers
verbatim:
- "What did you actually think when X happened?"
- "Why did you really stop doing Y? Not the tidy reason — the real one."
- "What's the part of this you'd argue with someone about?"
- "What did you get wrong that you'd rather not include?"
Tell him to type fast and not polish. His unpolished answers are the raw material for every voice-load-bearing sentence in the post. They will be flat, hedged, and specific — that flatness is the voice. Do not smooth it.
What ships with it
31 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/catch-22.md 7.2 KB
- references/comedians-set.md 5.4 KB
- references/compare-contrast.md 3.5 KB
- references/converging-ideas.md 6.1 KB
- references/existential-awakening.md 6.1 KB
- references/frameworks.md 2.5 KB
- references/freytags-pyramid.md 6.2 KB
- references/in-medias-res.md 6.7 KB
- references/kafkaesque-labyrinth.md 6.2 KB
- references/kishotenketsu.md 6.9 KB
- references/nested-loops.md 5.8 KB
- references/post-mortem.md 3.4 KB
- references/post-template.md 2.1 KB
- references/problem-agitation-solution.md 3.3 KB
- references/progressive-disclosure.md 3.3 KB
- references/reverse-chronology.md 7.6 KB
- references/scqa.md 2.8 KB
- references/sisyphean-arc.md 6.0 KB
- references/socratic-path.md 8.3 KB
- references/story-circle.md 7.4 KB
- references/strangers-report.md 6.7 KB
- references/the-false-start.md 6.5 KB
- references/the-metamorphosis.md 6.9 KB
- references/the-petal.md 6.6 KB
- references/the-rashomon.md 7.6 KB
- references/the-sparkline.md 6.6 KB
- references/the-spiral.md 7.1 KB
- references/the-waiting.md 7.2 KB
- references/three-act.md 5.1 KB
- references/voice-tone.md 6.5 KB
- scripts/slopcheck.py 11 KB runs code
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.
- 10d ago First seen · 156 lines · 78 tokens per session scan A 253e5c471b7a
blog-post-writer is a skill published in the GitHub repository nicknisi/claude-plugins (114 stars, last pushed 29d ago), licensed MIT. It adds 78 tokens to every session and 1,632 once invoked, about $0.0004 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…