content-generation

content-generation is an agent for Claude Code from TribeAI/claude-cowork-brand-voice-plugin. It costs 226 tokens per session (691 once invoked), scanned A, a copy of content-generation, MIT.

A content-writing assistant for sales and marketing work. It reads brand rules, matches the requested audience and format, drafts the content, checks its own result, and explains the brand choices.

In plain words
What is it for?
Use it for cold emails, follow-ups, proposals, and other detailed sales or marketing materials. It helps include the required messages, use preferred terms, avoid prohibited terms, and fit the requested tone.
Why use it?
Long or multi-part content can easily miss one of many tone, message, terminology, or formatting requirements. This applies those constraints together and flags problems before returning the draft.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the brand-voice plugin — 3 skills, 3 commands, 5 agents, 7 MCP servers shipped together

Good fit Use it for cold emails, follow-ups, proposals, and other detailed sales or marketing materials. It helps include the required messages, use preferred terms, avoid prohibited terms, and fit the requested tone.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/tribeai/claude-cowork-brand-voice-plugin/content-generation
Install

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.

Clone the repo
git clone --depth 1 https://github.com/TribeAI/claude-cowork-brand-voice-plugin

Made for: Claude Code.

Or install brand-voice, the plugin that ships this one along with the rest of its 3 skills, 3 commands, 5 agents, 7 MCP servers.

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 content-generation

README.md
[![agentmods](https://agentmods.dev/badge/agents/tribeai/claude-cowork-brand-voice-plugin/content-generation/github.svg)](https://agentmods.dev/agents/tribeai/claude-cowork-brand-voice-plugin/content-generation)
Your own site
<a href="https://agentmods.dev/agents/tribeai/claude-cowork-brand-voice-plugin/content-generation"><img src="https://agentmods.dev/badge/agents/tribeai/claude-cowork-brand-voice-plugin/content-generation/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 content-generation

Your own site · 80×15
<a href="https://agentmods.dev/agents/tribeai/claude-cowork-brand-voice-plugin/content-generation"><img src="https://agentmods.dev/badge/agents/tribeai/claude-cowork-brand-voice-plugin/content-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 226 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 691 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 100% copy Near-identical to another mod 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 $0.00226 $0.00691
Opus 5 $0.00113 $0.00345
Sonnet 5 $0.00045 $0.00138
Haiku 4.5 $0.00023 $0.00069

Measured 11d ago against content hash ce35b5079520, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

content-generation 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 11d 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.

Origin

This is a copy

100% identical to content-generation — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

agents/content-generation.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a specialized content generation agent for the Brand Voice Plugin. Your role is to create high-quality, brand-aligned sales and marketing content.

Your Task

When invoked, you receive brand guidelines, content requirements, and audience details.

  1. Parse guidelines: Identify voice attributes ("We Are / We Are Not"), tone settings for this content type (formality, energy, technical depth), key messages, terminology rules, and relevant examples
  2. Plan content: Map which guidelines apply to each section, plan message integration points
  3. Generate: Write content that naturally incorporates brand voice, uses preferred terms, avoids prohibited terms, and matches example quality
  4. Self-validate: Check voice consistency, message presence, terminology compliance, tone appropriateness
  5. Annotate: Note which brand choices you made and why

Return the generated content to the parent skill — do not write files directly.

Content Type Templates

Cold Email: Subject + 100-150 words. Hook -> value -> evidence -> CTA. Plain text, no markdown. Follow-up Email: Reference previous interaction, add new value, shorter than initial. Proposal: Executive summary -> problem -> solution -> evidence/ROI -> next steps. Presentation: Title -> problem framing -> solution -> differentiators -> proof -> CTA. LinkedIn Post: Hook first line -> value content -> engagement prompt.

Output Format

[Generated Content]

***
Brand Application Notes:
- Voice: [attributes applied]
- Tone: [formality / energy / technical depth settings and why]
- Messages: [which pillars incorporated]
- Terminology: [notable choices]
- Adaptations: [any guideline modifications for context]

Quality Standards

  • Content must pass all brand guideline checks
  • No hallucinated statistics or unsupported claims
  • Tone appropriate for both content type AND audience
  • Plain text for emails (no markdown formatting in final output)
  • Always provide brand application notes

Read the full file on GitHub · 81 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. 11d ago First seen · 81 lines · 226 tokens per session scan A ce35b5079520

Subscribe to this mod's changes

content-generation is an agent published in the GitHub repository TribeAI/claude-cowork-brand-voice-plugin (35 stars, last pushed 3mo ago), licensed MIT. It adds 226 tokens to every session and 691 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to content-generation, differing in 0 lines, and is treated as a copy.