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 glebis/humane-agentic-design --skill persona-reviewgit clone --depth 1 https://github.com/glebis/humane-agentic-designWrote 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/glebis/humane-agentic-design/persona-review)<a href="https://agentmods.dev/skills/glebis/humane-agentic-design/persona-review"><img src="https://agentmods.dev/badge/skills/glebis/humane-agentic-design/persona-review/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/glebis/humane-agentic-design/persona-review"><img src="https://agentmods.dev/badge/skills/glebis/humane-agentic-design/persona-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00094 | $0.00923 |
| Opus 5 | $0.00047 | $0.00462 |
| Sonnet 5 | $0.00019 | $0.00185 |
| Haiku 4.5 | $0.00009 | $0.00092 |
Grade A, and why
persona-review 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 11d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona Review
Announce at start: "I'm using the humane:persona-review skill to stress-test this document from stakeholder perspectives."
Overview
Takes a document and reviews it from N configurable personas. Each persona reads the document independently, provides structured feedback, then optionally the document is updated to address the feedback.
Usage
/persona-review [file-path] [personas]
Arguments:
file-path— path to the document to review (required). If omitted, ask user.personas— comma-separated persona names or "auto" (default: auto)
Examples:
/persona-review PRD.md engineer,designer,exec
/persona-review "Claude-Drafts/pitch-deck-script.md" auto
/persona-review # will ask for file and use auto personas
Workflow
Step 1: Load Document
Read the target file. Extract its purpose from context (frontmatter, filename, content).
Step 2: Select Personas
If auto: Choose 3 personas most relevant to the document type:
- PRD/spec → Skeptical Engineer, UX Designer, Business Stakeholder
- Pitch/proposal → Potential Customer, Investor, Competitor
- Blog post/article → Target Reader, Editor, Subject Expert
- Teaching material → Beginner Student, Advanced Practitioner, Curriculum Designer
- Marketing copy → Target Audience Member, Brand Skeptic, SEO Specialist
If specified: Use the named personas. Interpret flexibly — "engineer" becomes "Senior Engineer who has seen too many half-baked specs."
Step 3: Review Rounds
For each persona, generate a review with this structure:
### [Persona Name]
**Perspective:** [1-line description of who they are and what they care about]
**Reaction:** [2-3 sentences — their gut reaction on first read]
**Strengths:**
- [What works well from this perspective]
**Concerns:**
- [What's missing, unclear, or problematic]
**Key Question:** [The single most important question this persona would ask]
**Suggestion:** [One specific, actionable improvement]
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 119 lines · 94 tokens per session scan A 638f303dbeab
persona-review is a skill published in the GitHub repository glebis/humane-agentic-design (28 stars, last pushed today), licensed MIT. It adds 94 tokens to every session and 923 once invoked, about $0.0005 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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