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 synaptiai/prompt-decorators --skill prompt-decorators-usagegit clone --depth 1 https://github.com/synaptiai/prompt-decoratorsWrote 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/synaptiai/prompt-decorators/prompt-decorators-usage)<a href="https://agentmods.dev/skills/synaptiai/prompt-decorators/prompt-decorators-usage"><img src="https://agentmods.dev/badge/skills/synaptiai/prompt-decorators/prompt-decorators-usage/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/synaptiai/prompt-decorators/prompt-decorators-usage"><img src="https://agentmods.dev/badge/skills/synaptiai/prompt-decorators/prompt-decorators-usage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00063 | $0.01855 |
| Opus 5 | $0.00032 | $0.00928 |
| Sonnet 5 | $0.00013 | $0.00371 |
| Haiku 4.5 | $0.00006 | $0.00186 |
Grade A, and why
prompt-decorators-usage 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 11d 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Decorators Usage
This skill teaches when to suggest prompt decorators to the user and how to apply them - either as inline sigils, always-on config, or by switching on auto-decorate mode.
Prerequisites
- The
prompt-decoratorsplugin is installed (the user installed it from the Synapti marketplace). - The
UserPromptSubmithook is wired and active. - The decorator catalogue is available - browse with
/decorate listor/decorate search <term>. Counts below reflect the catalogue at the time this skill was written; run/decorate listfor the current set.
Workflow
Use TodoWrite to track these steps when invoked from another workflow:
Step 1: Identify the decoration intent
Match the user's prompt to one of the catalogue's core categories.
All decorator names below are verified against the vendored registry at
claude-code-plugin/vendor/prompt_decorators/registry/core/ at the
time this skill was written. The catalogue grows and names can
change; if any suggestion below doesn't appear in /decorate list, trust
the CLI over this table and use /decorate search <term> or
/decorate list <category> to find the current equivalent.
| Category | Trigger phrases in the prompt | Real decorators (verified) |
|---|---|---|
| reasoning | "why", "explain", "analyze", "compare", "pros/cons", "trade-offs" | TreeOfThought, FirstPrinciples, RedTeam, Socratic, RootCause, Debate, Contrarian, Abductive, Deductive, Inductive, BlindSpots |
| structure | "list", "outline", "summarize", "table", "bullet", "organize" | Outline, Summary, TableFormat, Comparison, Bullet, Layered, Nested, DecisionMatrix, Prioritize, Timeline |
| tone | "concise", "brief", "detailed", "academic", "formal", "simple" | Concise, Detailed, Academic, ELI5, Professional, AsExpert, Audience, Persona, Creative, Narrative |
| verification | "verify", "fact-check", "cite", "sources", "evidence", "risks" | CiteSources, FactCheck, Confidence, Uncertainty, Limitations, Balanced, Steelman, FindGaps, PeerReview |
| minimal (base layer) | "standard output format", "baseline reasoning shape" | OutputFormat, Reasoning, StepByStep, Tone, Version |
| meta | composing decorators or controlling their interaction | Override, Chain, Conditional, Refine, Priority, BuildOn, Extension |
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.
- 11d ago First seen · 186 lines · 63 tokens per session scan A 20fbf5bf88f5
prompt-decorators-usage is a skill published in the GitHub repository synaptiai/prompt-decorators (43 stars, last pushed 3d ago), licensed Apache-2.0. It adds 63 tokens to every session and 1,855 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
image-generation
Enhances image generation prompts with Subject-Context-Style structure, style anchors, character consistency, mcp-image workflows. Not for video generation, TTS, FFmpeg, audio, or design-to-code.
add-prompt
Scaffold a new MCP prompt template. Use when the user asks to add a prompt, create a reusable message template, or define a prompt for LLM interactions.
openclaw-prompt-enhancer
Remote prompt engineering MCP server with 6 tools that turn weak prompts into powerful ones. Use when: (1) 'improve this prompt' or 'make my prompt better', (2) 'score this prompt' or 'rate prompt quality', (3) 'convert prompt to Claude format' or 'translate for Gemini', (4) 'generate system prompt' or 'create…
add-prompt
Scaffold a new MCP prompt template. Use when the user asks to add a prompt, create a reusable message template, or define a prompt for LLM interactions.
add-prompt
Scaffold a new MCP prompt template. Use when the user asks to add a prompt, create a reusable message template, or define a prompt for LLM interactions.
add-prompt
Scaffold a new MCP prompt template. Use when the user asks to add a prompt, create a reusable message template, or define a prompt for LLM interactions.