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 mhrsdev/AI-Agent-Skills-Library --skill writing-beatsgit clone --depth 1 https://github.com/mhrsdev/AI-Agent-Skills-LibraryWrote 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/mhrsdev/ai-agent-skills-library/writing-beats)<a href="https://agentmods.dev/skills/mhrsdev/ai-agent-skills-library/writing-beats"><img src="https://agentmods.dev/badge/skills/mhrsdev/ai-agent-skills-library/writing-beats/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/mhrsdev/ai-agent-skills-library/writing-beats"><img src="https://agentmods.dev/badge/skills/mhrsdev/ai-agent-skills-library/writing-beats.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 | $0.00028 | $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 12d 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.
- 12d ago First seen · 68 lines · 28 tokens per session scan A 668185cfb6eb
writing-beats is a skill published in the GitHub repository mhrsdev/AI-Agent-Skills-Library (6 stars, last pushed 2mo 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
agent-orchestrator
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
android-ui-journey-testing
XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
anti-duplication
Before implementing new code (endpoints, components, services, models), search the codebase for existing patterns to reuse. Prevent code duplication by finding and suggesting similar implementations. Auto-trigger when user asks to create, implement, add, or build new functionality.
breaking-change-detector
Detect and warn about breaking API/schema changes before implementation. Auto-trigger when modifying API routes, database schemas, or public interfaces. Validates changes against api-strategy.md versioning rules. Suggests migration paths for breaking changes. Prevents removing endpoints, changing request/response…
hallucination-detector
Detect and prevent hallucinated technical decisions during feature work. Auto-trigger when suggesting technologies, frameworks, APIs, database schemas, or external services. Validates all tech decisions against docs/project/tech-stack.md (single source of truth). Blocks suggestions that violate documented…