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 vinnie357/claude-skills --skill topiarygit clone --depth 1 https://github.com/vinnie357/claude-skillsWrote 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/vinnie357/claude-skills/topiary)<a href="https://agentmods.dev/skills/vinnie357/claude-skills/topiary"><img src="https://agentmods.dev/badge/skills/vinnie357/claude-skills/topiary/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/vinnie357/claude-skills/topiary"><img src="https://agentmods.dev/badge/skills/vinnie357/claude-skills/topiary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 125 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00040 | $0.02240 |
| Opus 5 | $0.00020 | $0.01120 |
| Sonnet 5 | $0.00008 | $0.00448 |
| Haiku 4.5 | $0.00004 | $0.00224 |
Grade A, and why
topiary 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 6d 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 — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Topiary
Topiary is a universal code formatter that uses Tree-sitter grammars and queries to define formatting rules. Rather than implementing language-specific formatting logic, Topiary uses declarative Tree-sitter query files (.scm) to specify how code should be formatted.
Key Concepts
Tree-Sitter Queries
Tree-sitter is a parser generator that creates language parsers from grammar definitions. Topiary uses Tree-sitter queries to analyze code structures and apply formatting rules. Queries match patterns in the syntax tree using S-expression syntax and decorate matched nodes with capture names (prefixed with @) that describe formatting actions.
Query Files and Capture Names
Language formatting is defined in .scm (Scheme) query files. Each capture name instructs Topiary how to format the matched node:
- Line breaks:
@prepend_hardline,@append_hardline(always insert newline),@prepend_empty_softline,@append_empty_softline(newline or nothing),@prepend_spaced_softline,@append_spaced_softline(newline or space) - Indentation:
@prepend_indent_start,@append_indent_start,@prepend_indent_end,@append_indent_end(mark indentation scopes) - Spacing:
@prepend_space,@append_space(add single space) - Control:
@delete(remove matched node),@do_nothing(suppress default behavior),@leaf(prevent formatting within node) - Input-aware:
@prepend_input_softline,@append_input_softline(preserve original line break presence)
Idempotency
Topiary formatting is idempotent—running the formatter repeatedly on already-formatted code produces identical output. This guarantee allows safe integration into version control hooks and CI pipelines.
Author Intent Preservation
Topiary respects the structural intent of code by preserving language-specific semantics. It focuses on whitespace, indentation, and line breaks rather than restructuring code. This approach works especially well with languages whose semantics are simple and whitespace-independent.
What ships with it
2 files 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.
- 6d ago First seen · 367 lines · 40 tokens per session scan A 0cf50cf2fe00
topiary is a skill published in the GitHub repository vinnie357/claude-skills (25 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 2,240 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 2026-09-04.
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