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 slide-thesis-mappergit 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/slide-thesis-mapper)<a href="https://agentmods.dev/skills/biolytics-ai/rhetoric-engine/slide-thesis-mapper"><img src="https://agentmods.dev/badge/skills/biolytics-ai/rhetoric-engine/slide-thesis-mapper.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.00854 |
| Opus 5 | $0.00020 | $0.00427 |
| Sonnet 5 | $0.00008 | $0.00171 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
slide-thesis-mapper 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slide Thesis Mapper
Convert an argument spine into slide-level audience questions and answer theses. This is a hard gate before design, rendering, or deck compilation.
Do not create visual layouts, speaker notes, or finished slides until the thesis map is approved.
Inputs
- Approved intent brief.
- Approved insight artifact.
- Approved argument spine with evidence needs and rebuttals.
- Presentation format, duration, audience setting, and any slide count constraints.
- Required sections, mandated content, or existing deck structure if applicable.
Outputs
Return a Slide Thesis Map with:
slide_thesis_map: each slide or segment with audience question, answer thesis, proof job, and source/evidence need.section_roadmap: section sequence, purpose, transition logic, and approximate time allocation.backup_slide_topics: optional detail, evidence, appendix, or rebuttal slides.time_fit_notes: pacing risks, compression options, expansion options, and likely cuts.
Use this compact format:
## Slide Thesis Map
- Section roadmap:
- Slide thesis map:
- Backup slide topics:
- Time fit notes:
- Approval questions:
Workflow
- Translate each argument branch into the audience question it must answer.
- Write one answer thesis per slide or segment. Each thesis must be a complete sentence with a claim.
- Assign a proof job to each slide: establish context, prove branch, compare options, resolve objection, show implication, or drive action.
- Group slides into sections that match audience logic and the argument spine.
- Add transitions that explain why the next question follows from the previous answer.
- Move deep detail, edge cases, and defensive proof into backup slide topics.
- Check time fit against duration, complexity, and expected discussion.
- Mark unresolved evidence needs or unclear theses before allowing design or compilation.
- Ask for approval and treat changes to the spine as upstream revisions.
Evaluation Checks
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 · 85 lines · 41 tokens per session scan A 64f0c67a6c87
slide-thesis-mapper is a skill published in the GitHub repository Biolytics-AI/rhetoric-engine (1 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 854 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.
Other skills, from other repositories
spec-kitty-charter-doctrine
Run charter interview, generation, context, and sync workflows for project governance in Spec Kitty 3.x. Access doctrine artifacts programmatically via DoctrineService. Resolve agent profiles. Load action-scoped governance context iteratively, not all at once. Triggers: "interview for charter", "generate charter"…
mongodb-query-optimizer
Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query…
polar-local-environment
This skill should be used when setting up or managing Polar local development environment with Docker.
neo4j-modeling-skill
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with…
lov-article-creator
A skill that turns source material or a draft into a complete, branded WeChat public-account article package.
lov-repo2docs
Turn any folder of source material — a code repository, a pile of articles, a mixed knowledge dump with images — into a professional, polished Fumadocs (Next.js) documentation website, then deploy it to https://{product-id}.example.com/docs. Works by reading the folder one unit at a time and incrementally growing and…