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blog post pipeline
A gated 8-stage editorial pipeline that enforces fact-checking, brand voice, and multi-role adversarial review.
Free
blog post pipeline
Example session with this skill installed
I need to start a new blog post about the benefits of memory-safe languages for legacy systems. The target is our 'Engineering Insights' blog. Start the brief and research stages.
- Read your context and instructions
- Compiled the blog post pipeline
I have initialized the post directory and completed the research phase. The process is currently halted at the Curation gate for your approval of the gathered facts.
Post Pipeline: Memory-Safe Languages
| Stage | Status | Output File | Action |
|---|---|---|---|
| 0. Brief | Complete | posts/memory-safe-legacy/00-config.md | Defined target: Engineering Insights |
| 1. Research | Complete | posts/memory-safe-legacy/01-research.md | Found 12 sources, 4 primary benchmarks |
| 2. Curation | Pending | posts/memory-safe-legacy/02-curated.md | Awaiting human selection |
Research Summary
I have categorized the findings into three key pillars. Please review the 01-research.md file and select which points should move to the drafting stage.
Key Pillar 1: CVE Reduction Statistics
- Source [1]: CISA report on memory safety vulnerabilities (approx 70% of deep vulnerabilities).
- Source [2]: Google/Microsoft case studies on Rust adoption.
Key Pillar 2: Performance Overheads
- Source [3]: Benchmarks comparing C++ manual management vs. Rust/Swift runtime checks.
- Source [4]: Impact analysis on legacy hardware constraints.
Key Pillar 3: Integration Patterns
- Source [5]: Best practices for FFI (Foreign Function Interface) with legacy C codebases.
- Source [6]: Incremental migration strategies (strangler fig pattern).
Next steps
- Open
posts/memory-safe-legacy/01-research.mdto review all 12 citations. - Create
posts/memory-safe-legacy/02-curated.mdcontaining only the facts you want the writer to use. - Update the
statusin00-config.mdtocuratedto enable the Drafting stage.
Connects securely to your tools. The creator never sees your data.
About this skill
Manual blog production often suffers from hallucinated facts, drifting brand voice, and fragmented workflows. This skill implements a rigorous, gated editorial pipeline that enforces truth and consistency across multiple publications.
What it does
- Enforces veracity by blocking any quantitative or comparative claims that lack a cited source from the research phase.
- Isolates roles to prevent the writer from researching or the reviewer from self-editing, ensuring objective adversarial oversight.
- Manages state via a file-based system, allowing you to pause and resume complex content projects across different sessions.
- Handles localization through cultural adaptation rather than literal translation, keeping the message intact across languages.
- Automates publishing including image planning, asset uploads, and final Markdown deployment to target repositories.
How it works
- Initialize the brief by creating a configuration file that defines the blog target and primary goals.
- Execute research and curation where the agent gathers sources and the human selects which facts are approved for the draft.
- Generate and review the draft, triggering a specialized adversarial pass that flags unsourced claims as blockers.
- Finalize and publish by optionally translating the content, planning media, and pushing to the target environment.
Frameworks & tools
The skill is designed for environments with filesystem access like Claude Code or Cursor. It uses YAML for brand configuration and maintains state through a structured Markdown file hierarchy.
Why this beats prompting it yourself
Generic prompts often lead to "hallucinated expertise" where the AI invents statistics to sound persuasive. this skill forces a structural separation between fact-finding and prose generation, making it impossible for the agent to include unverified data.
Use cases
- Technical content marketing requiring precise performance benchmarks and cited specifications.
- Bilingual blog management where posts must be adapted for different cultural contexts while maintaining a single source of truth.
- High-volume editorial teams needing a repeatable, audited process for multi-author or multi-brand environments.
Known limitations
Requires initial manual setup of a blogs.yaml file for brand voice and hard limits. Does not support automated chaining of stages; a human must approve each gate to progress the state.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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