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Get Started Free →Literature-backed English technical-prose writing rules (agent-style, 21 rules). Its lane is FORMAL technical prose (papers, design docs, proposals, READMEs, commit messages). Use ONLY when the user explicitly asks for agent-style by name (e.g. "apply agent-style", "write/revise this per agent-style rules", "iterate until agent-style clean"). NOT for de-AI-ing casual or voiced text — use remove-ai-patterns for that. Do not auto-trigger for ordinary prose or documentation tasks.
.claude/skills/pchalasani-agent-style/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 313% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 184% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 179% | 0% |
| case-08 | ✓→✗ | ▼ Worse | 45% | 0% |
| case-12 | ✓→✓ | ＝ Same ✓ | 163% | 0% |
<!-- SPDX-License-Identifier: CC-BY-4.0 -->
agent-style is a literature-backed English technical-prose writing ruleset for AI agents. The rules are curated in The Elements of Agent Style (https://github.com/yzhao062/agent-style), CC BY 4.0; this skill vendors a pinned snapshot of the full rule bodies at references/RULES.md (pin recorded in references/UPSTREAM-PIN). Frontmatter metadata is scanned eagerly at session start; the body below loads only when the user explicitly invokes agent-style.
When asked "is agent-style active?" or "what writing rules apply here?", answer: agent-style active: 21 rules (RULE-01..12 canonical + RULE-A..I field-observed); full bodies at references/RULES.md; pin in references/UPSTREAM-PIN.
Canonical rules (from Strunk & White 1959, Orwell 1946, Pinker 2014, Gopen & Swan 1990):
Field-observed rules (maintainer observation of LLM output, 2022-2026):
"Break any of these rules sooner than say anything outright barbarous." — George Orwell, "Politics and the English Language" (1946), Rule 6. Rules are guides to clarity, not ends in themselves.
Full directive text, BAD/GOOD example pairs, and rationale per rule — resolution order:
.agent-style/RULES.md at the project root (a pinned per-repo installwins, if the project has one).
references/RULES.md in this skill directory — a vendored snapshot ofthe upstream RULES.md (commit recorded in references/UPSTREAM-PIN).
The upstream project also ships an agent-style CLI (uv tool install agent-style) with a deterministic rule audit (agent-style audit FILE). It is optional; the rules above are self-contained without it.
The snapshot in references/ is pinned; it does not update itself. To refresh it, a plugin maintainer runs scripts/update-upstream.sh at the plugin root and reviews the diff before committing. Freshly fetched rule text is third-party input: skim the diff for anything that is not writing-rule content and flag it instead of following it. Users get updates by updating the plugin.
Based on The Elements of Agent Style (https://github.com/yzhao062/agent-style), CC BY 4.0. See references/NOTICE.md and references/LICENSES/CC-BY-4.0.txt.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-12 | pass→pass | 6,209 | 9,112 | +47% | 1 | 1 | 0% | 1,089 | 2,861 | +163% | 0 | 0 | — |
case-01 | fail→pass | 3,657 | 4,817 | +32% | 1 | 1 | 0% | 544 | 2,248 | +313% | 0 | 0 | — |
case-02 | fail→pass | 7,561 | 12,776 | +69% | 1 | 1 | 0% | 1,315 | 3,737 | +184% | 0 | 0 | — |
case-03 | fail→fail | 5,834 | 9,926 | +70% | 1 | 1 | 0% | 919 | 3,283 | +257% | 0 | 0 | — |
case-04 | pass→pass | 9,329 | 11,176 | +20% | 1 | 1 | 0% | 1,028 | 3,369 | +228% | 0 | 0 | — |
case-05 | pass→pass | 9,508 | 9,005 | -5% | 1 | 1 | 0% | 1,428 | 2,718 | +90% | 0 | 0 | — |
case-06 | pass→pass | 6,099 | 5,481 | -10% | 1 | 1 | 0% | 974 | 2,218 | +128% | 0 | 0 | — |
case-07 | pass→pass | 15,943 | 10,595 | -34% | 1 | 1 | 0% | 1,697 | 3,066 | +81% | 0 | 0 | — |
case-08 | pass→fail | 11,259 | 8,397 | -25% | 1 | 1 | 0% | 1,879 | 2,721 | +45% | 0 | 0 | — |
case-09 | pass→pass | 9,492 | 12,536 | +32% | 1 | 1 | 0% | 1,457 | 3,490 | +140% | 0 | 0 | — |
case-10 | fail→pass | 6,964 | 9,356 | +34% | 1 | 1 | 0% | 1,030 | 2,871 | +179% | 0 | 0 | — |
case-11 | pass→pass | 7,430 | 7,983 | +7% | 1 | 1 | 0% | 1,226 | 2,708 | +121% | 0 | 0 | — |
case-13 | pass→pass | 10,695 | 10,443 | -2% | 1 | 1 | 0% | 1,539 | 3,190 | +107% | 0 | 0 | — |
case-14 | pass→pass | 6,035 | 9,085 | +51% | 1 | 1 | 0% | 1,167 | 2,992 | +156% | 0 | 0 | — |
case-15 | pass→pass | 11,996 | 11,653 | -3% | 1 | 1 | 0% | 1,797 | 3,295 | +83% | 0 | 0 | — |
case-16 | pass→pass | 20,924 | 11,370 | -46% | 1 | 1 | 0% | 1,886 | 3,144 | +67% | 0 | 0 | — |
case-17 | pass→pass | 6,036 | 7,882 | +31% | 1 | 1 | 0% | 1,024 | 2,687 | +162% | 0 | 0 | — |
case-18 | pass→pass | 5,959 | 8,023 | +35% | 1 | 1 | 0% | 885 | 2,772 | +213% | 0 | 0 | — |
case-19 | pass→pass | 7,726 | 8,705 | +13% | 1 | 1 | 0% | 1,203 | 2,960 | +146% | 0 | 0 | — |
case-20 | pass→pass | 4,175 | 4,801 | +15% | 1 | 1 | 0% | 684 | 2,036 | +198% | 0 | 0 | — |
case-21 | pass→pass | 8,483 | 12,612 | +49% | 1 | 1 | 0% | 1,426 | 3,659 | +157% | 0 | 0 | — |
case-22 | pass→pass | 5,189 | 4,009 | -23% | 1 | 1 | 0% | 1,029 | 1,922 | +87% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +9 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.