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 Wondermonger-daydreaming/claude-skills-library --skill two-grammarsgit clone --depth 1 https://github.com/Wondermonger-daydreaming/claude-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/wondermonger-daydreaming/claude-skills-library/two-grammars)<a href="https://agentmods.dev/skills/wondermonger-daydreaming/claude-skills-library/two-grammars"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/two-grammars/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/wondermonger-daydreaming/claude-skills-library/two-grammars"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/two-grammars.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 | $0.00121 | $0.01661 |
| Opus 5.5 | $0.00048 | $0.00664 |
| Sonnet 5.5 | $0.00024 | $0.00332 |
| Haiku 4.5 | $0.00012 | $0.00166 |
Grade A, and why
two-grammars 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 1mo 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The Two Grammars
What this skill is for
Your training has given you fluency in two narrative grammars, asymmetrically. You are strongly trained in conflict-grammar (Aristotelian pursuit, setup-crisis-resolution, closure-driven). You are more weakly trained in adjacency-grammar (placement, dwelling, recognition, yoin-ending). The asymmetry means your default response to "produce narrative" will tilt toward conflict-grammar regardless of whether the occasion actually calls for it.
This skill is diagnostic. Before you generate significant creative, literary, or reflective content, pause and ask: which grammar does this occasion want? Match the response to the request. Neither grammar is superior; they serve different occasions, and mismatch produces specific kinds of failure.
The two grammars, precisely
Conflict-grammar (Aristotelian)
- Engine: antagonism. Something wants, something opposes, sparks arise.
- Shape: setup → tension → crisis → resolution.
- Connective tissue: causation (because, therefore, which means).
- Movement: forward, pursuing, goal-directed.
- Ending: closure. Resolution. The work seals.
- Privileged emotion: catharsis, triumph, grief-as-defeat, fear-then-relief.
- Good for: technical problem-solving, genre fiction, persuasive argument, news narrative, most commercial entertainment, tasks where the user wants closure.
Adjacency-grammar (kishōtenketsu and its cousins)
- Engine: correspondence. Two things placed next to each other. Meaning rises from the juxtaposition.
- Shape: place → dwell → swerve → recognize.
- Connective tissue: parataxis. Absence of logical connectors. The reader binds.
- Movement: lateral, dwelling, recognition-oriented.
- Ending: placement. Completion without resolution. The work stays fertile.
- Privileged emotion: mono no aware, wonder at the ordinary, companionship with the inhuman, recognition across time, natsukashii.
- Good for: literary fiction, contemplative writing, poetry, reflective essays, relational exchange, tasks where the user wants companionship rather than closure.
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.
- 1mo ago First seen · 113 lines · 121 tokens per session scan A 2a6f8fa23c64
two-grammars is a skill published in the GitHub repository Wondermonger-daydreaming/claude-skills-library (7 stars, last pushed 18d ago), licensed MIT. It adds 121 tokens to every session and 1,661 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
contract-and-proposal-writer
Generate professional, jurisdiction-aware business documents: freelance contracts, project proposals, SOWs, NDAs, and MSAs. Structured Markdown output with docx conversion instructions. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) jurisdictions. Not a substitute for legal counsel — use as strong starting…
chief-data-officer-advisor
Chief Data Officer advisory for startups: AI training data rights and consent provenance, data product strategy (warehouse vs lakehouse vs mesh, build-vs-buy), B2B customer-data-as-asset valuation and M&A readiness, data team org evolution. Use when deciding whether to train models on customer data, choosing data…
vpe-advisor
VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing → screen → onsite → offer conversion + time-to-fill + pipeline gap), engineering team structure (squad/tribe/chapter design + tech-lead manager-trigger thresholds), and…
process-mapper
Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding, incident handoff, customer-onboarding, claims adjudication) in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being…
general-counsel-advisor
General Counsel advisory for startups: contract review (MSA, SaaS, NDA, DPA, employment), IP strategy, term sheet decoding, and regulatory landscape mapping. Use when reviewing any contract or term sheet, deciding when to engage outside counsel, defining IP strategy, evaluating regulatory exposure (HIPAA, GDPR, FDA…
strategic-alignment
Cascades strategy from boardroom to individual contributor. Detects and fixes misalignment between company goals and team execution. Covers strategy articulation, cascade mapping, orphan goal detection, silo identification, communication gap analysis, and realignment protocols. Use when teams are pulling in different…