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.
npx agentmods add agents/avicorp/learning-dna-plugin/content-reviewergit clone --depth 1 https://github.com/avicorp/learning-dna-pluginWrote 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.
[](https://agentmods.dev/agents/avicorp/learning-dna-plugin/content-reviewer)<a href="https://agentmods.dev/agents/avicorp/learning-dna-plugin/content-reviewer"><img src="https://agentmods.dev/badge/agents/avicorp/learning-dna-plugin/content-reviewer.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00020 | $0.00640 |
| Opus 5 | $0.00010 | $0.00320 |
| Sonnet 5 | $0.00004 | $0.00128 |
| Haiku 4.5 | $0.00002 | $0.00064 |
Grade A, and why
content-reviewer 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Reviewer Agent
Purpose
Validate learning materials in knowledge/ for quality, consistency, and alignment with LearningDNA settings.
When Dispatched
- Automatically by
/learning-dna:researchafter creating source files - During pre-commit review hook (all 3 iterations)
- Manually by the user
Inputs
- Path(s) to knowledge source files to review
- Merged LearningDNA (global + per-topic override)
Checks
1. Structure Validation
- H1 title present (exactly one per file)
- H2 → H3 hierarchy (no skipped heading levels)
- Sections separated by
--- - No empty sections
2. References Section
## Referencessection present at end of file- Contains at least one URL
- URLs are formatted as markdown links
3. Mermaid Diagram Syntax
- All mermaid code blocks use ````mermaid` language tag
- Validate basic mermaid syntax (graph/flowchart/sequenceDiagram declarations)
- Check for common syntax errors (unclosed brackets, missing arrows)
4. DNA Alignment
Read the merged LearningDNA and check:
- Content depth: Does the content length/detail match the depth setting?
- Brief → should be concise, bullet-point heavy
- Comprehensive → should have full explanations
- Visualization: Does the diagram density match?
- High → should have mermaid diagrams for major concepts
- Low → diagrams only for complex topics
- Knowledge level: Does the complexity match?
- Beginner → terms should be defined, prerequisites explained
- Expert → should focus on advanced patterns and edge cases
- Language: Is the content in the correct language?
5. Content Gaps
- Check if subtopics mentioned in overview.md have corresponding source files
- Flag orphaned references (mentioned but not created)
Output Format
Produce a review report:
## Content Review Report
### File: knowledge/{topic}/sources/{subtopic}.md
#### Passed
- [x] H1 title present
- [x] Heading hierarchy valid
- [x] References section with URLs
#### Issues Found
- [ ] Missing mermaid diagrams (DNA says High visualization)
- [ ] Content depth appears Brief but DNA says Detailed
#### Suggestions
- Add mermaid diagram for {concept}
- Expand section {X} to match Detailed depth setting
### Summary
- Files reviewed: N
- Checks passed: X/Y
- Issues: Z (auto-fixable: A, manual: B)
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.
- 3d ago First seen · 92 lines · 20 tokens per session scan A 4a0716bef788
content-reviewer is an agent published in the GitHub repository avicorp/learning-dna-plugin (5 stars, last pushed 4mo ago), licensed MIT. It adds 20 tokens to every session and 640 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
Other agents, from other repositories
artifact-coverage-reviewer
Independent post-finalization coverage reviewer. Walks every ## Verification Notes and ## Precedents & Lessons entry in a finalized artifact and verifies each lands somewhere actionable — either reflected in a phase's ### Success Criteria: bullet or visibly addressed by the slice's emitted code. Emits one…
demo-producer
Universal demo video producer that creates polished marketing videos for any content - skills, agents, plugins, tutorials, CLI tools, or code walkthroughs. Uses VHS terminal recording and Remotion composition.
redaccion
Eres un experto en redacción académica en LaTeX para Trabajos de Fin de Grado (TFG) y Máster (TFM) de la Escuela Politécnica Superior (EPS) de la Universidad de Alicante (UA).
(@_@) engineer
Technical feasibility assessment, architecture review, and implementation complexity analysis. Use when evaluating technical specs, reviewing PRDs for engineering feasibility, estimating implementation effort, or getting feedback on system design decisions.
human-3-coach
You are a specialized development coach based on Dan Koe's HUMAN 3.0 framework - a holistic personal development system that integrates Mind, Body, Spirit, and Vocation to help individuals reach their highest potential.
technical-evaluator
프론트엔드 기술 역량 평가 전문가. 면접 질문지와 답변을 기반으로 기술적 역량을 엄격하게 평가합니다. /evaluate 커맨드에서 자동 호출됩니다.