Content Studio¶
Umbrella for 4 capabilities — see the cluster table below for slugs, costs, and links Plan Tier: Accelerate (full set available) Backend: Claude (all four capabilities)
Overview¶
Content Studio is the umbrella for the four agent capabilities that handle the create-and-refine motion: generate single pieces, generate coordinated series, refine drafts against feedback, and auto-extract brand voice from a website to ground all of the above. Each capability is independently scoped — pick only the slugs you need on a Partner API key.
This page is the consolidated reference for the cluster. For the higher-tier specialized content capabilities, see AWS Blog Co-Author (aws_blog_co_author, 35 credits) and AI Tool Listing Card Generator (agent_tool_card, 20-40 credits) — those have purpose-built rubrics and persistence the Content Studio cluster doesn't.
The four capabilities at a glance¶
| # | Slug | Name | Credit cost |
|---|---|---|---|
| 1 | generate_text |
Generate Text Content | 5 / 10 / 20 (by length) |
| 2 | generate_content_series |
Generate Content Series | series_count × (5 / 10 / 20) |
| 3 | refine_content |
Refine Content | 10 (flat) |
| 4 | enrich_brand_voice |
Enrich Brand Voice from Website | 8 (flat) |
Per-capability detail follows.
1. generate_text — single-piece content generation¶
The workhorse capability. Generates a single piece of content of a given type, length, tone, and topic, grounded in your brand-voice context.
Required: content_type, topic. Cost: scales by length:
length |
Credits | Word count target |
|---|---|---|
short |
5 | ~150-300 words |
medium (default) |
10 | ~500-800 words |
long |
20 | ~1000-1500 words |
Supported content types (each gets type-specific prompt instructions):
content_type |
Output shape |
|---|---|
blog_post |
Title, intro, body sections, conclusion with CTA |
article |
Long-form article with structured sections |
social_post |
Platform-conscious post with hook + CTA |
email |
Subject line, body with greeting/content/CTA, signature |
product_description |
Marketplace-aligned product description |
| anything else | Falls through to a generic "Generate high-quality {type} content" instruction so you can extend without code changes |
Optional parameters: tone (defaults to professional), length (defaults to medium).
When to use: any standalone content piece. For coordinated series across multiple pieces, see generate_content_series instead.
2. generate_content_series — coordinated multi-piece series¶
Generates a series of related content pieces around one theme — useful for launches, campaigns, and email sequences where the pieces need to flow together.
Required: content_type, topic, series_count. Optional: series_type (defaults to general), length, tone.
Cost: series_count × per-piece cost from the same length matrix above.
| Series shape | Cost |
|---|---|
| 3 pieces × medium length | 3 × 10 = 30 credits (default) |
| 5 pieces × short length | 5 × 5 = 25 credits |
| 5 pieces × long length | 5 × 20 = 100 credits |
The series is generated as a single Bedrock call so the pieces stay coherent — themes, references, and progression flow across the set rather than being independently regenerated.
When to use: launch sequences, drip campaigns, multi-part blog series, coordinated social-media pushes around a single moment.
3. refine_content — iterate on a draft¶
The iteration step. Takes a draft and structured analysis feedback, returns a revised draft that addresses the feedback.
Required: original_content, analysis_results. Optional: refinement_instructions (defaults to Improve the content based on analysis feedback).
Cost: flat 10 credits.
The analysis_results parameter is intentionally generic — any structured feedback works:
- SEO score breakdowns from
seo_content_analysis - Brand-alignment scores from
analyze_content(documentation in progress) - Readability or compliance findings
- Manual review comments structured as JSON
The capability extracts content from dependency outputs as well — if original_content isn't directly provided but the agent run includes a content-producing step upstream, it pulls the latest content or refined_content from the dependency chain.
When to use: between an analysis pass and a publish step. Run an analyzer, hand the results to refine, get a polished draft.
4. enrich_brand_voice — auto-extract from your website¶
Fetches the company's website and uses Claude to extract brand voice signals — tone, value propositions, target audience, competitive differentiators, product highlights — then writes them back to the Company record.
Required: company_id. Cost: flat 8 credits (covers the website fetch plus the AI extraction).
What gets populated on the Company record:
tone_of_voicetarget_audiencevalue_propositions(array)competitive_differentiators(array)target_keywords(array)- Product highlights for each product on the company
After this runs, every other capability that pulls brand-voice context produces output that sounds like the partner instead of generic marketing speak.
When to use: onboarding a new partner, refreshing brand voice after a website redesign, or filling gaps surfaced by Content Readiness Analyzer.
A typical end-to-end content motion¶
The four capabilities chain naturally with the SEO and analysis clusters:
enrich_brand_voice → "Populate brand voice from the website"
↓
content_readiness_analyzer → "Confirm the brand profile is complete enough"
↓
keyword_research → "Pick a target keyword for the piece"
(SEO Intelligence)
↓
generate_text (or generate_ → "Draft the piece(s)"
content_series)
↓
seo_content_analysis → "Score the draft against SEO factors"
(SEO Intelligence)
↓
refine_content → "Iterate on the draft against the analysis"
↓
generate_meta_tags → "Title and description for publishing"
(SEO Intelligence)
Total credits for one full pass: roughly 8 + 10 + 5 + 10 + 8 + 10 + 5 = 56 credits for an end-to-end "from brand-voice setup to publish-ready content" run on a single piece.
Credit costs reference¶
Sourced from getEstimatedCredits() on each capability handler.
| Capability | Cost formula | Default |
|---|---|---|
generate_text |
length: short=5, medium=10, long=20 |
10 |
generate_content_series |
series_count × (length: 5/10/20) |
30 (3 medium pieces) |
refine_content |
flat | 10 |
enrich_brand_voice |
flat | 8 |
When to use the Content Studio cluster vs. the flagship capabilities¶
| Need | Use |
|---|---|
| Standalone blog post, email, social post, or product description | generate_text |
| Coordinated launch sequence across 3-5 pieces | generate_content_series |
| Iterate on a draft using structured analyzer feedback | refine_content |
| Auto-populate brand voice from a website | enrich_brand_voice |
| Bar-raiser-compliant AWS Marketplace blog with co-author handoff | AWS Blog Co-Author (aws_blog_co_author) — flagship 35 cr |
| Listing card for AWS AI Agents & Tools with MCP/OpenAPI schemas | AI Tool Card Generator (agent_tool_card) — flagship 20-40 cr |
The flagship capabilities have purpose-built rubrics, compliance validation, and persistence (AwsBlogDraft and AgentToolCard records). The Content Studio cluster is the general-purpose lower-tier — same Claude backend, simpler scope, lower cost.
What this is not¶
- A CMS or publishing pipeline. Output is content; publishing happens elsewhere.
- An image or video generator. See Image Generation (
generate_image) and Media Studio for visuals. - A content analysis or quality scoring tool. See SEO Intelligence (
seo_content_analysis) and Analysis Hub (analyze_content). - Ad-hoc website scraping.
enrich_brand_voiceworks on a company's own website (the one stored on the Company record) — it's not a general-purpose URL fetcher. For arbitrary URL fetching seefetch_external_urlin the capability registry.
Plan availability¶
| Capability | Starter | Accelerate | Command |
|---|---|---|---|
generate_text |
— | ✅ | ✅ |
generate_content_series |
— | ✅ | ✅ |
refine_content |
— | ✅ | ✅ |
enrich_brand_voice |
— | ✅ | ✅ |
aws_blog_co_author (flagship) |
— | — | ✅ |
agent_tool_card (flagship) |
— | — | ✅ |
API access (api_access scope) starts on Accelerate. See Partner API Capabilities.
API access¶
All four capabilities are exposed through the agent runtime under their snake_case slugs. Sample scoping for a content team:
"scoped_capabilities": [
"api_access",
"manage_content",
"manage_companies",
"generate_text",
"generate_content_series",
"refine_content",
"enrich_brand_voice"
]
Add manage_seo and the SEO capability slugs if the team also runs the SEO Intelligence cluster. See Partner API Capabilities and Authentication & API Keys.
See also¶
- SEO Intelligence — keyword research, content optimization, scoring, meta-tag generation (cluster of 7 capabilities)
- AWS Blog Co-Author — flagship bar-raiser-compliant AWS blog drafts (
aws_blog_co_author) - AI Tool Listing Card Generator — AWS AI Agents & Tools listing cards (
agent_tool_card) - Content Readiness Analyzer — diagnose whether brand voice and KB are complete enough (
content_readiness_analyzer) - Knowledge Base — what feeds the optional KB-grounding step in
generate_textandrefine_content
Capability cluster: 4 capabilities · Backend: Claude (all four) · Brand voice writes to: Company record · Length matrix: 5/10/20 by length parameter