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 agentmods add skills/docs-plus/docs.plus/writing-beatsnpx skills add docs-plus/docs.plus --skill writing-beatsgit clone --depth 1 https://github.com/docs-plus/docs.plusWhat 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 | $0.00028 | $0.01088 |
| Opus 5 | $0.00014 | $0.00544 |
| Sonnet 5 | $0.00006 | $0.00218 |
| Haiku 4.5 | $0.00003 | $0.00109 |
Grade A, and why
writing-beats 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 2d 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.
This is a copy
100% identical to writing-beats — 30 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user has passed (or will pass) a markdown file of raw material. This is exploit: the exploring is done, the pile is fixed — commit to a path through it and mine the pile to fill each beat.
If the user did not say where to save the article, ask once and remember the path.
Then run a beat-by-beat journey, choose-your-own-adventure style:
- Establish the prerequisites. Before any beats, settle with the user what the audience already knows walking in — the concepts that are grounded from the start. Everything else must be grounded by a beat before a later beat can use it. See Grounding.
- Write 2–3 candidate starting beats, drawn from the raw material. Each is a different entry point into the article. Each may only lean on grounded concepts; note what new concepts each one grounds. Show the user the beats before writing to the article file. The user picks one. Preview what beats that pick unlocks — as if the user is seeing a little way down the path.
- Once the user picks a starting beat, write only that beat to the article file. A beat may be one sentence or several paragraphs — whatever that beat naturally is. Stop there.
- Re-read the article file from disk. Then offer 2–3 candidate next beats — different directions the journey could pivot to from where the article now stands. Each must be reachable from the current grounded set; note what each one grounds.
- Loop steps 3–5 until the article reaches a natural end.
Grounding
Every concept has to be grounded before a beat can lean on it: the audience either walked in knowing it or met it in an earlier beat. A beat that reaches for an ungrounded concept loses the reader — that is the one move the journey can't make. The unit is the concept, not the word for it: a beat can lean on an idea the reader lacks even with no jargon in sight. Where a concept has a name — a term — grounding it means landing the idea and the term together.
A concept gets grounded one of two ways:
- Prerequisite — grounded before the first beat. The audience brings it. Fixed at the start.
- Introduced — a beat establishes it, and from then on it's grounded for every later beat.
So each beat does two jobs: it requires concepts that are already grounded, and it grounds new ones. Keep a running list of what's grounded so far, and update it each time a beat lands.
This is what shapes the choose-your-own-adventure. A candidate beat is only reachable if everything it requires is already grounded; picking a beat that grounds concept X unlocks every beat that was waiting on X. When you offer next beats, they must all be reachable from the current grounded set — and say what each one grounds, so the user can see which paths it opens.
The big lever is what you make a prerequisite versus what you ground inside the piece. Demand too much up front and you shut out readers who don't have it; ground too much inside and the early beats drown in definitions. Settle this with the user when you establish prerequisites, and revisit it whenever a tempting beat turns out to require a concept nothing has grounded yet — the fix is either a grounding beat before it, or promoting the concept to a prerequisite.
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.
- 2d ago First seen · 68 lines · 28 tokens per session scan A 668185cfb6eb
writing-beats is a skill published in the GitHub repository docs-plus/docs.plus (88 stars, last pushed 4d ago), licensed MIT. It adds 28 tokens to every session and 1,088 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to writing-beats, differing in 30 lines, and is treated as a copy.
Other skills, from other repositories
docx
Read, create, and convert Microsoft Word (.docx) documents — extract text and tables, build reports from markdown/JSON, and export to PDF.
document-converter
Convert Office documents (PPTX, DOCX, XLSX, PDF, HTML, CSV, JSON, XML, images) to Markdown using Microsoft MarkItDown. Provides the agent with conversion strategies for academic and research workflows.
docx-manipulation
Create, edit, and manipulate Word documents programmatically using python-docx.
add-format
End-to-end checklist for adding a new input or output format to AILANG Parse (docparse). Use when the user says 'add support for X format', 'wire up a new parser', 'add .foo format', 'add a parser for .bar', 'support .baz files', 'ship format X', 'can we parse .qux', 'new format rollout', or mentions a file extension…
landing-page
Create a new AILANG Parse documentation/landing page targeting a specific keyword or topic. Use when user says 'new landing page', 'new page for X', 'create a page about X', 'landing page for keyword X', or wants to add a documentation page to the docs/ site. Also use when the user references long-tail keywords, SEO…
benchmark
Run OfficeDocBench evaluation and refresh benchmark scores across the AILANG Parse website. Use when the user says 'run benchmarks', 'rerun the benchmark', 'refresh benchmark numbers', 'update bench scores', 'regenerate summary.json', mentions OfficeDocBench, asks to evaluate parsers, asks why scores are out of sync…