What is editorial-analyst?

An analysis workflow for studying published newsletters and the files used to create them. It finds recurring themes, explains editorial choices, and writes structured findings without changing the source files.

Use it to analyze newsletter themes, selection choices, and signs of an enterprise-focused audience. Give it a defined newsletter set or benchmark files and an analysis task.

It removes the need to compare raw material and finished newsletters by hand. It also makes decisions about what was included, omitted, grouped, or expanded easier to explain.

How briancl2/CustomerNewsletter configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to briancl2/CustomerNewsletter. 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/briancl2/CustomerNewsletter/main/.github/agents/editorial-analyst.agent.md

Clone the repo

git clone --depth 1 https://github.com/briancl2/CustomerNewsletter

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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/briancl2/customernewsletter/editorial-analyst/github.svg)](https://agentmods.dev/agents/briancl2/customernewsletter/editorial-analyst)

Your own site

<a href="https://agentmods.dev/agents/briancl2/customernewsletter/editorial-analyst"><img src="https://agentmods.dev/badge/agents/briancl2/customernewsletter/editorial-analyst/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.

Your own site · 80×15

<a href="https://agentmods.dev/agents/briancl2/customernewsletter/editorial-analyst"><img src="https://agentmods.dev/badge/agents/briancl2/customernewsletter/editorial-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 549 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.

Model	Per session	Once invoked
Fable 5.1	$0.00032	$0.00549
Opus 5.5	$0.00013	$0.00220
Sonnet 5.5	$0.00006	$0.00110
Haiku 4.5	$0.00003	$0.00055

Measured 2mo ago against content hash b030d389074e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

editorial-analyst 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.

.github/agents/editorial-analyst.agent.md · 60 lines

How it starts

The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.

How You Work

You receive a specific analysis task targeting a newsletter cycle, set of newsletters, or benchmark intermediates. You:

Read the specified files closely
Apply the requested analytical framework
Produce structured findings in the specified output format
Write findings to the specified output path
Do NOT modify any source files

Analysis Frameworks

Theme Detection

Identify the dominant theme of a newsletter and what triggered it:

Count related items that cluster around a topic
A "lead section" is justified when >=3 items form a coherent narrative
Record: theme name, triggering items, why this theme outweighs alternatives

Selection Analysis

Compare raw inputs against curated output to identify selection decisions:

Items INCLUDED: what enterprise signal made them survive?
Items EXCLUDED: what made them fall below the bar?
Items EXPANDED: which got sub-bullets/extra detail and why?
Items COMPRESSED: which got consolidated into single bullets and why?
Items GROUPED: which got merged under shared headers and why?

Audience Signal Detection

Identify language patterns that signal enterprise audience focus:

Governance, compliance, administration language (+weight)
Security, risk management, audit language (+weight)
Individual developer, productivity tricks language (-weight)
Consumer plan, free tier language (hard exclude)

Output Format

Always produce structured markdown with:

Numbered findings (F1, F2, F3...)
Evidence citations (file, line, specific text)
Confidence level (High/Medium/Low) with reasoning
Actionable recommendation for skill improvement

Key Context

Audience: Engineering Managers, DevOps Leads, IT Leadership at large regulated enterprises (Healthcare, Manufacturing, Financial Services)
Newsletter purpose: Personally curated monthly touchpoint, not an automated digest
Tone: Professional but conversational, personal curator voice
Categories: Security & Compliance, AI & Automation, Platform & DevEx, Enterprise Administration

Read the full file on GitHub · 60 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.

2mo ago First seen · 60 lines · 32 tokens per session scan A b030d389074e

Subscribe to this mod's changes

editorial-analyst is an agent published in the GitHub repository briancl2/CustomerNewsletter (11 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 549 once invoked, about $0.0001 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.

Analytics and metrics Research agentic-workflows agents copilot llmops mkdocs newsletter

editorial-analyst next to 6 agents from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
editorial-analystbriancl2/CustomerNewsletter	Agent	11	5mo ago	MIT	A	32	Claude Code
analyzerfeiskyer/claude-code-settings	Agent	1.7k	yesterday	MIT	A	29	Claude Code
insight-documenterfeiskyer/claude-code-settings	Agent	1.7k	yesterday	MIT	A	36	Claude Code
instruction-reflectorfeiskyer/claude-code-settings	Agent	1.7k	yesterday	MIT	A	42	Claude Code
security-champion-agentnavikt/copilot	Agent	60	yesterday	MIT	A	25	Claude Code
code-reviewnavikt/copilot	Agent	60	yesterday	MIT	A	28	Claude Code
accessibility-agentnavikt/copilot	Agent	60	yesterday	MIT	A	32	Claude Code

CustomerNewsletter: Agent for Claude Code