content-workflow: Skill for Claude Code

.claude/skills/review/SKILL.md

review is a skill for Claude Code from robinsadeghpour/content-workflow. It costs 79 tokens per session (1,852 once invoked), scanned A, original, MIT.

A morning command-line review for choosing which discovered content ideas to keep, skip, or mark as especially important.

In plain words
What is it for?
It helps show the day’s discovery results, load pending ideas from the database, and prepare selected ideas for content generation.
Why use it?
It gives a focused way to process the backlog instead of leaving ideas scattered in a database or review files.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool; mentions Claude Code.

This is robinsadeghpour/content-workflow's own configuration. It tells Claude Code how to work on content-workflow 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 content-workflow configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is node scripts/review-update.js --id <actual_idea_id> --status <actual_status>.

Reuse

Borrowing it

Nothing to install: this file belongs to robinsadeghpour/content-workflow. 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/robinsadeghpour/content-workflow/main/.claude/skills/review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/robinsadeghpour/content-workflow

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 review

README.md
[![agentmods](https://agentmods.dev/badge/skills/robinsadeghpour/content-workflow/review/github.svg)](https://agentmods.dev/skills/robinsadeghpour/content-workflow/review)
Your own site
<a href="https://agentmods.dev/skills/robinsadeghpour/content-workflow/review"><img src="https://agentmods.dev/badge/skills/robinsadeghpour/content-workflow/review/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 review

Your own site · 80×15
<a href="https://agentmods.dev/skills/robinsadeghpour/content-workflow/review"><img src="https://agentmods.dev/badge/skills/robinsadeghpour/content-workflow/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,852 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.
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 $0.00079 $0.01852
Opus 5.5 $0.00032 $0.00741
Sonnet 5.5 $0.00016 $0.00370
Haiku 4.5 $0.00008 $0.00185

Measured 2mo ago against content hash b4b8f35b0a18, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

review 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.

.claude/skills/review/SKILL.md · 218 lines

How it starts

The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review -- Morning Batch Content Review

Interactive morning review workflow for KEEP/SKIP/STAR decisions on discovered content ideas. One focused pass through the backlog, ~5 minutes, then hand off to content generation.

Workflow

When /review is invoked, execute the following steps in order.


Step 1: Check for today's review file

Run:

cat data/review/$(date +%Y-%m-%d).md 2>/dev/null

If the file exists, display a brief summary to Robin:

"Today's pulse found {N} ideas. Here's the overview:"

Then show the file content (or a condensed version with titles and sources).

If no file exists, tell Robin:

"No pulse has run today. Run /pulse first, or I can review ideas from previous days."

Continue to Step 2 regardless — there may be pending ideas in the DB from earlier pulse runs.


Step 2: Query pending ideas from the database

Run:

node -e "
  const db = require('better-sqlite3')('data/content.db');
  const ideas = db.prepare(\"SELECT id, title, summary, source_url, source_type, score, status, transcript FROM ideas WHERE status IN ('new', 'starred') ORDER BY score DESC\").all();
  console.log(JSON.stringify(ideas));
  db.close();
"

Parse the JSON output. If the array is empty, tell Robin:

"No pending ideas to review. All caught up! Run /pulse to discover new ideas."

Stop here if nothing to review.


Step 3: Present ideas and collect decisions

Initialize counters: kept=0, skipped=0, starred=0, remaining=total_count.

For each idea (iterate in order, score DESC):

Display this format:

--- Idea {N}/{total} ---

{title}

Source: {source_type} | {source_url}
Angle:  {content_angle_suggestion}

> {summary}

[Transcript available: yes/no]

Content angle suggestion logic (evaluate in order, first match wins):

  • source_type === 'changelog' → "News reaction"
  • title contains (case-insensitive) "tutorial", "how to", "guide", or "learn" → "Tutorial breakdown"
  • title contains (case-insensitive) "wrong", "actually", "unpopular", "hot take", or "controversial" → "Hot take"
  • title contains (case-insensitive) "vs", "compare", "comparison", or "better" → "Comparison"
  • default → "Topic breakdown"

Read the full file on GitHub · 218 lines

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. 2mo ago First seen · 218 lines · 79 tokens per session scan A b4b8f35b0a18

Subscribe to this mod's changes

review is a skill published in the GitHub repository robinsadeghpour/content-workflow (54 stars, last pushed 6mo ago), licensed MIT. It adds 79 tokens to every session and 1,852 once invoked, about $0.0003 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 2026-08-30.

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