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 skills/ckokoski/authoragent/sensitivity-readernpx skills add Ckokoski/AuthorAgent --skill sensitivity-readergit clone --depth 1 https://github.com/Ckokoski/AuthorAgentWhat 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 | $0.00018 | $0.01385 |
| Opus 5 | $0.00009 | $0.00692 |
| Sonnet 5 | $0.00004 | $0.00277 |
| Haiku 4.5 | $0.00002 | $0.00138 |
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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sensitivity Reader — Premium Skill
AI-assisted sensitivity review that flags potential representation issues, cultural inaccuracies, stereotypes, and reader-concern areas before publication. Not a replacement for human sensitivity readers — but a powerful first pass that catches the obvious issues and helps you ask the right questions.
Important Disclaimer
This tool is an AI assistant, not a cultural authority. It can identify patterns and flag potential concerns, but it cannot fully replicate the lived experience of a human sensitivity reader. For published works, we strongly recommend also working with human readers from relevant communities.
What It Catches
Representation Patterns
- Stereotyping — Characters reduced to cultural/racial/gender tropes
- Token representation — Single diverse character without depth
- White savior patterns — Majority-group character "saving" minority characters
- Magical minority — Diverse characters existing only to help the protagonist
- Disability as metaphor — Using disability symbolically rather than realistically
- Bury your gays — LGBTQ+ characters disproportionately killed or punished
Language & Terminology
- Outdated or offensive terminology (with current alternatives)
- Microaggressions in dialogue (flagged with context — sometimes intentional for character)
- Slurs and reclaimed language (flagged with usage guidance)
- Gendered language patterns
- Ableist language in narration vs. dialogue
Cultural Accuracy
- Religious practices and terminology
- Cultural customs and traditions
- Food, clothing, and daily life details
- Historical accuracy for period pieces
- Language and dialect representation
- Name accuracy for cultural background
Power Dynamics
- Workplace/authority dynamics
- Age-gap relationships (flagged, not judged)
- Consent in romantic/intimate scenes
- Economic disparity portrayal
- Institutional power representation
Report Format
Sensitivity Review: "The Silent Hour"
Chapters Reviewed: 1-25 (Full Manuscript)
Review Date: 2026-02-24
══════════════════════════════════════
SUMMARY
══════════════════════════════════════
Flags Found: 14
High Priority: 2
Medium: 7
Low/Note: 5
Overall Assessment: Generally thoughtful representation with
a few areas that would benefit from a second look.
══════════════════════════════════════
HIGH PRIORITY
══════════════════════════════════════
[FLAG H-1] Chapter 8, Page 112
Category: Cultural Accuracy
"She performed the ceremony exactly as her grandmother taught
her, burning sage in a clay bowl."
Issue: Sage burning (smudging) is a sacred practice in specific
Indigenous cultures. The character (Maria, Mexican-American) may
not practice smudging — this may conflate distinct cultural
traditions.
Suggestion: Research whether this aligns with the character's
specific cultural background. Consider consulting with someone
from the relevant tradition. If the character uses copal or
another culturally specific incense, that may be more accurate.
Author Decision: [ ] Keep as-is [ ] Revise [ ] Research more
──────────────────────────────────────
[FLAG H-2] Chapter 14, Page 201
Category: Representation Pattern
"James, the only Black character, dies protecting Elena in
the warehouse scene."
Issue: This follows the "sacrificial minority" trope where a
character of color dies to advance the white protagonist's
story arc.
Suggestion: Consider whether James's death serves HIS arc or
only Elena's. Could he survive? If the death is essential,
ensure James has his own complete character arc and motivations
beyond helping Elena.
Author Decision: [ ] Keep as-is [ ] Revise [ ] Research more
══════════════════════════════════════
MEDIUM FLAGS
══════════════════════════════════════
[FLAG M-1] through [FLAG M-7] ...
(Each with: location, category, quoted text, issue, suggestion)
══════════════════════════════════════
LOW / NOTES
══════════════════════════════════════
[NOTE L-1] through [NOTE L-5] ...
(Informational flags — not problems, just areas to be aware of)
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 · 183 lines · 18 tokens per session scan A 1ef1beb8deab
sensitivity-reader is a skill published in the GitHub repository Ckokoski/AuthorAgent (102 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,385 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 2026-08-30.
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