llm-wiki-newsroom: Skill for Claude Code

.claude/skills/journalism-writing/SKILL.md

journalism-writing is a skill for Claude Code from alfadur7/llm-wiki-newsroom. It costs 95 tokens per session (2,054 once invoked), scanned A, original, MIT.

A writing guide for clear journalism and argument-based explainers. It covers ways to structure a story, explain the central issue, present opposing positions fairly, and assess the strength of an argument.

In plain words
What is it for?
Use it to write or review news explainers, issue analyses, arguments, and landscape overviews with clear structure, fair presentation, and explicit reasoning.
Why use it?
It helps turn complex or disputed subjects into readable pieces without hiding the main point or overstating certainty. It also provides checks for balance and evidence-based reasoning.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is alfadur7/llm-wiki-newsroom's own configuration. It tells Claude Code how to work on llm-wiki-newsroom itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything llm-wiki-newsroom configures →

Reuse

Borrowing it

Nothing to install: this file belongs to alfadur7/llm-wiki-newsroom. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/alfadur7/llm-wiki-newsroom/main/.claude/skills/journalism-writing/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/alfadur7/llm-wiki-newsroom

Made for: Claude Code.

Wrote 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.

agentmods badge for journalism-writing

README.md
[![agentmods](https://agentmods.dev/badge/skills/alfadur7/llm-wiki-newsroom/journalism-writing/github.svg)](https://agentmods.dev/skills/alfadur7/llm-wiki-newsroom/journalism-writing)
Your own site
<a href="https://agentmods.dev/skills/alfadur7/llm-wiki-newsroom/journalism-writing"><img src="https://agentmods.dev/badge/skills/alfadur7/llm-wiki-newsroom/journalism-writing/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.

agentmods 80×15 button for journalism-writing

Your own site · 80×15
<a href="https://agentmods.dev/skills/alfadur7/llm-wiki-newsroom/journalism-writing"><img src="https://agentmods.dev/badge/skills/alfadur7/llm-wiki-newsroom/journalism-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,054 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00095 $0.02054
Opus 5 $0.00048 $0.01027
Sonnet 5 $0.00019 $0.00411
Haiku 4.5 $0.00010 $0.00205

Measured 12d ago against content hash 8dae0c619494, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

journalism-writing 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.

The scan reads SKILL.md. This mod also ships 1 executable file (checks.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.claude/skills/journalism-writing/SKILL.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

journalism-writing

Writing craft drawn from news/explanatory journalism and argumentation traditions — narrative lead (Lede→Nut graph→Kicker), dialectical structure (thesis·antithesis·synthesis), argument quality (Toulmin), and fairness (BBC due impartiality). criteria.json is the SoT for each criterion's definition, comparator, and source. The shared parsing and wiki-global state that the deterministic checks (judge=A) rely on are injected by the orchestrator (the skill is content-type-agnostic). Examples are illustrative of the target English prose.

Dialectic structure (jrn.thesis-antithesis · jrn.c-section-size · jrn.c-stance-naming · jrn.monitoring-balance)

Develop an issue as Hegelian thesis → antithesis → synthesis. State thesis and antithesis with explicit Position A / Position B bold labels (ko rendering: A 입장 / B 입장); add a C — Mediation label (ko: C 중재) only when a genuine convergence exists. The C paragraph must not run longer than the longer of A and B, so the convergence is not mistaken for the main clash. If C is not a synthesis but a meta-critique (weakening both sides at once, flagging interest bias), move it out of the dialectic frame — a meta-critique in the C slot breaks the three-part structure.

Synthesis does not pick a winner. In Hegel's terms it sublates — cancels and preserves — identifying what each side correctly grasps. Concretely, place each side's monitoring point (what one would observe if that side were right) symmetrically (jrn.monitoring-balance); a monitor skewed to one side hides an editorial verdict under hedged wording (combine with BBC due impartiality). e.g. ✅ "If tighter regulation is right, we would observe reduced consumer harm; if looser regulation is right, increased new entry" (winning conditions symmetric on both sides) / ❌ "Regulation blocks innovation, so abolishing it is right" (one-sided verdict).

Argument quality (jrn.toulmin-claim · jrn.rebuttal · jrn.qualifier)

Check each side's support structure with the Toulmin model (claim · grounds/data · warrant · qualifier · rebuttal · backing).

Read the full file on GitHub · 57 lines

Files

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.

Changes

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.

  1. 12d ago First seen · 57 lines · 95 tokens per session scan A 8dae0c619494

Subscribe to this mod's changes

journalism-writing is a skill published in the GitHub repository alfadur7/llm-wiki-newsroom (85 stars, last pushed yesterday), licensed MIT. It adds 95 tokens to every session and 2,054 once invoked, about $0.0005 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.

Related

Other skills, from other repositories

binder-modeling

Binder data modeling — define entity types, fields, relations, constraints, views, and navigation. Use when asked to "create a type", "add a field", "define a schema", "set up relations", "model entities", "create a view", "set up navigation", "render entities as files", or design a binder workspace schema.

mpazik/Binder · 74 tokens

binder-app

Build a small HTTP app (dashboard, kanban board, admin panel, custom UI) on top of an existing Binder workspace. Use when asked to "create an app", "build a dashboard", "show records in a chart", "make a kanban/board", "build an admin panel", or "add a UI on top of binder".

mpazik/Binder · 74 tokens

binder-import

Import external data into a Binder workspace. Handles CSV, JSON, YAML, Markdown files, and directories of Markdown. Use when asked to "import data", "load records from a file", "ingest documents", "migrate data into binder", or bulk-create records from an external source.

mpazik/Binder · 62 tokens

binder-cli

Binder CLI for knowledge graph operations — CRUD, search, schema inspection, transaction import, docs rendering. Use when asked to "query binder", "search records", "create a record", "check the schema", "import transactions", "undo changes", or work with a binder workspace.

mpazik/Binder · 60 tokens

capture-task

Capture a new task — create a draft or pending Task record from a rough idea or detailed spec. Use when asked to "add a task", "log a bug", "create a task", or "add to backlog".

mpazik/Binder · 48 tokens

refine-backlog

Refine the backlog — screen drafts, remove duplicates, fill in missing details, classify, link, and move to pending.

mpazik/Binder · 29 tokens