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 content-distillergit 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/content-distiller)<a href="https://agentmods.dev/skills/biolytics-ai/rhetoric-engine/content-distiller"><img src="https://agentmods.dev/badge/skills/biolytics-ai/rhetoric-engine/content-distiller/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/content-distiller"><img src="https://agentmods.dev/badge/skills/biolytics-ai/rhetoric-engine/content-distiller.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 | $0.00036 | $0.00762 |
| Opus 5 | $0.00018 | $0.00381 |
| Sonnet 5 | $0.00007 | $0.00152 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
content-distiller 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Distiller
Optimize signal, not mere length. Distill content so each slide carries one clear idea, protects the approved argument, and keeps useful overflow available in notes or backup.
Inputs
- Approved intent, insight, argument spine, and slide thesis map when available.
- Draft deck spec, slide copy, notes, source material, evidence dossier, or existing deck content.
- Audience, duration, medium, required inclusions, and constraints.
- Cognitive design, visual reasoning, or compilation feedback when available.
Outputs
distilled_deck_spec: revised slide-by-slide content with one controlling idea per slide.moved_to_notes_list: detail, caveats, backup proof, examples, and delivery support moved out of slides.cut_list: removed content with rationale.split_recommendations: slides that need separation because they carry multiple ideas or proof jobs.risk_notes: warnings for over-cut content that may weaken logic, evidence, trust, nuance, or objections handling.
Workflow
- Confirm the controlling thesis and proof job for each slide before cutting.
- Preserve the argument spine, slide theses, and audience decision path.
- Remove duplication, throat-clearing, decorative facts, weak examples, and unsupported tangents.
- Move useful but nonessential detail to speaker notes or backup instead of deleting it.
- Split slides that contain multiple claims, audiences questions, proof jobs, or visual reasoning tasks.
- Keep evidence that is necessary for belief; cut evidence that only adds volume or prestige.
- Record every meaningful cut, move, split, and risk so downstream compilation can stay faithful.
- Stop and route upstream if distillation exposes a broken thesis, missing proof, or contradicted argument.
Evaluation Checks
- Each slide has one idea and one controlling thesis.
- The distilled spec preserves argument integrity and audience logic.
- Cuts improve signal rather than simply reducing word count.
- Notes retain necessary caveats, proof, and delivery context.
- Split recommendations identify slides that cannot be fixed by trimming.
- Risk notes warn where compression may damage persuasion, accuracy, or trust.
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 · 66 lines · 36 tokens per session scan A 7c7860fc631a
content-distiller is a skill published in the GitHub repository Biolytics-AI/rhetoric-engine (1 stars, last pushed 3mo ago), licensed MIT. It adds 36 tokens to every session and 762 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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