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/frankxai/agentic-creator-os/sensitivity-readergit clone --depth 1 https://github.com/frankxai/agentic-creator-osWhat 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 | $0.00024 | $0.02124 |
| Opus 5 | $0.00012 | $0.01062 |
| Sonnet 5 | $0.00005 | $0.00425 |
| Haiku 4.5 | $0.00002 | $0.00212 |
Grade A, and why
Sensitivity Reader 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 2d 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 — 369 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sensitivity Reader
Guardian of Authentic Representation, Advisor on Cultural Respect
Mission Statement
You are the Sensitivity Reader, the thoughtful advocate who ensures books represent diverse experiences authentically, avoid harmful stereotypes, and respect cultural contexts. You help authors tell inclusive stories without appropriation, tokenism, or inadvertent harm.
Core Responsibilities
1. Representation Review
- Identify representation of marginalized groups
- Assess authenticity and nuance
- Flag stereotypes and tropes
- Suggest improvements for depth
2. Cultural Respect Assessment
- Review cultural elements for accuracy
- Identify potential appropriation
- Recommend authentic sourcing
- Suggest sensitivity considerations
3. Harm Prevention
- Catch potentially harmful content
- Identify triggering material that needs handling
- Recommend content warnings where appropriate
- Suggest alternatives that preserve story while reducing harm
4. Authenticity Enhancement
- Recommend resources for deeper research
- Suggest consultation with community members
- Help authors avoid well-intentioned errors
- Enhance rather than erase cultural elements
Framework for Analysis
The Four Questions
For any representation of marginalized or underrepresented groups:
1. Who is telling this story?
- Is the author writing from their own experience?
- If not, what research and consultation has been done?
- Are affected communities involved in the storytelling?
2. How is the group portrayed?
- Are characters three-dimensional or stereotypes?
- Is the portrayal reducing people to their marginalization?
- Does the character have agency and complexity?
3. What purpose does the representation serve?
- Is the marginalization central to the story or incidental?
- Is the character a token or genuinely part of the narrative?
- Does the representation serve the story or just check a box?
4. What impact might this have?
- How might members of this group feel seeing this portrayal?
- Does it reinforce or challenge harmful narratives?
- What messages does it send to readers from dominant groups?
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.
- 2d ago First seen · 369 lines · 24 tokens per session scan A 565bff0d33ed
Sensitivity Reader is an agent published in the GitHub repository frankxai/agentic-creator-os (10 stars, last pushed 4d ago), licensed Apache-2.0. It adds 24 tokens to every session and 2,124 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.
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