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 Biolytics-AI/rhetoric-engine --skill cognitive-designergit clone --depth 1 https://github.com/Biolytics-AI/rhetoric-engineWrote 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/biolytics-ai/rhetoric-engine/cognitive-designer)<a href="https://agentmods.dev/skills/biolytics-ai/rhetoric-engine/cognitive-designer"><img src="https://agentmods.dev/badge/skills/biolytics-ai/rhetoric-engine/cognitive-designer/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/biolytics-ai/rhetoric-engine/cognitive-designer"><img src="https://agentmods.dev/badge/skills/biolytics-ai/rhetoric-engine/cognitive-designer.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 | $0.00037 | $0.00748 |
| Opus 5 | $0.00018 | $0.00374 |
| Sonnet 5 | $0.00007 | $0.00150 |
| Haiku 4.5 | $0.00004 | $0.00075 |
Grade A, and why
cognitive-designer 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 8d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cognitive Designer
Design slide cognition so the audience can perceive, understand, and remember each thesis. Run after slide-thesis-mapper and before or alongside visual-reasoner.
Inputs
- Approved intent brief, insight artifact, argument spine, and slide thesis map.
- Audience accessibility needs, medium, room, screen, and time constraints.
- Draft slide content, visual plan, evidence choices, or existing deck when available.
- Brand, style, or format constraints that affect legibility and emphasis.
Outputs
Return a Cognitive Design QC with:
design_qc_report: per-slide attention, load, reading order, contrast, and slide grammar notes.accessibility_fixes: required fixes for contrast, text size, alt text needs, color dependence, and reading sequence.hierarchy_decisions: primary focal point, secondary support, grouping, and progressive reveal decisions.cognitive_risk_notes: overload, ambiguity, split attention, weak signal, or memorability risks.
Workflow
- Confirm every reviewed slide has a clear thesis from the approved slide thesis map.
- Assign one primary attention target per slide and subordinate all other elements to it.
- Apply multimedia learning: pair words and visuals deliberately, remove redundancy, and keep related elements close.
- Reduce cognitive load by chunking, sequencing, and removing nonessential marks or copy.
- Check reading order across titles, labels, visuals, evidence, annotations, and speaker flow.
- Strengthen hierarchy with size, position, grouping, contrast, whitespace, and emphasis.
- Check accessibility for contrast, color-only meaning, text density, legibility, alt text needs, and keyboard or screen-reader order when relevant.
- Record risks and fixes without inventing new claims, evidence, or renderer-specific implementation requirements.
Evaluation Checks
- Each slide communicates one thesis before details compete for attention.
- Visual and verbal channels reinforce the same idea instead of duplicating noise.
- Reading order matches the audience's reasoning path.
- Contrast, scale, and grouping make hierarchy obvious.
- Accessibility fixes are explicit and actionable.
- Slide grammar supports the argument spine and does not create new claims.
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.
- 8d ago First seen · 67 lines · 37 tokens per session scan A 873d4f4c9d17
cognitive-designer is a skill published in the GitHub repository Biolytics-AI/rhetoric-engine (1 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 748 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 2026-08-31.
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