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 skills add Owl-Listener/inclusive-design-skills --skill audit-storiesgit clone --depth 1 https://github.com/Owl-Listener/inclusive-design-skillsWrote 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/skills/owl-listener/inclusive-design-skills/audit-stories)<a href="https://agentmods.dev/skills/owl-listener/inclusive-design-skills/audit-stories"><img src="https://agentmods.dev/badge/skills/owl-listener/inclusive-design-skills/audit-stories/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/owl-listener/inclusive-design-skills/audit-stories"><img src="https://agentmods.dev/badge/skills/owl-listener/inclusive-design-skills/audit-stories.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00046 | $0.00423 |
| Opus 5 | $0.00023 | $0.00211 |
| Sonnet 5 | $0.00009 | $0.00085 |
| Haiku 4.5 | $0.00005 | $0.00042 |
Grade A, and why
audit-stories 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 12d 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.
What it actually says
Audit User Stories for Inclusion
Review an existing set of user stories and identify where disability and diverse abilities have been overlooked — then add the missing criteria without creating separate accessibility tickets.
Process
Step 1: Gather Stories
Collect the user stories to audit. This could be a sprint backlog, a feature's full story set, or an epic.
Step 2: Check Each Story
Using inclusive-user-stories, review each story's acceptance criteria for:
- Keyboard operability
- Screen reader support
- Visual accessibility (contrast, colour independence, zoom)
- Motor accessibility (target size, timing, precision)
- Cognitive accessibility (plain language, error recovery, undo)
Flag any story where one or more of these are missing.
Step 3: Check for Assumption Bias
Using edge-case-identification, for each story ask:
- What input method does this assume?
- What sensory ability does this assume?
- What cognitive capacity does this assume?
- What context does this assume?
- What "edge cases" have been dismissed that are daily reality for some users?
Step 4: Add Missing Criteria
For each flagged story, write the specific acceptance criteria that need to be added. Don't create separate stories — add directly to the existing ones.
Output
Deliver an audit report:
- Summary — number of stories reviewed, number with gaps, most common gap type
- Story-by-story findings — each story with its missing criteria listed
- Added criteria — the specific acceptance criteria to add to each story, ready to paste into the backlog
- Patterns — recurring gaps that suggest a systemic issue (e.g., "no story in this sprint mentions keyboard access")
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.
- 12d ago First seen · 55 lines · 46 tokens per session scan A d7c5f88db263
audit-stories is a skill published in the GitHub repository Owl-Listener/inclusive-design-skills (98 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 423 once invoked, about $0.0002 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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