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 devinilabs/pro-skill --skill thinking-orbsgit clone --depth 1 https://github.com/devinilabs/pro-skillWrote 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/devinilabs/pro-skill/thinking-orbs)<a href="https://agentmods.dev/skills/devinilabs/pro-skill/thinking-orbs"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/thinking-orbs/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/devinilabs/pro-skill/thinking-orbs"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/thinking-orbs.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 | $0.00088 | $0.02195 |
| Opus 5 | $0.00044 | $0.01097 |
| Sonnet 5 | $0.00018 | $0.00439 |
| Haiku 4.5 | $0.00009 | $0.00219 |
Grade A, and why
thinking-orbs 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 5d 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 thinking-orbs — 0 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Thinking Orbs
Core Contract
- Use
thinking-orbsin React 18+ interfaces that need indeterminate AI activity feedback. - Map the real product lifecycle to one of the six shipped states.
- Use only the tuned
20or64pixel size. Do not stretch one preset into another. - Keep
theme="auto"unless the surrounding surface has a known fixed theme. - Pair the orb with concise visible status text when the activity matters to the user.
- Override
aria-labelwith a task-specific label, or hide the orb from assistive technology when adjacent live text already announces the same state. - Use
pausedto freeze the current frame. Do not simulate pause withspeed={0}. - Treat the orb as indeterminate feedback, never as a progress percentage or completion signal.
The package renders monochrome dots on a transparent 2D canvas. It does not expose custom colors, arbitrary sizes, or determinate progress.
Install
Inspect the project package manager, then install:
npm install thinking-orbs
The package declares react and react-dom version 18 or newer as peer dependencies. Import the component and exported types from the package root:
import {
ThinkingOrb,
type OrbSize,
type OrbState,
type OrbTheme,
type ThinkingOrbProps,
} from "thinking-orbs";
Choose the State
working— generic tool execution, multi-step work, or an activity without a more precise state.searching— retrieval, web search, file search, or knowledge lookup.solving— reasoning, analysis, calculation, or planning.listening— microphone input, speech capture, or waiting for a spoken turn.composing— writing, summarizing, drafting, or generating a text response.shaping— creating or refining an image, layout, structured artifact, or other formed output.
Prefer a truthful generic working state over a visually interesting but inaccurate state. Change the state only when the underlying activity changes.
Choose the Size
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.
- 5d ago First seen · 243 lines · 88 tokens per session scan A 6c24fc7f6582
thinking-orbs is a skill published in the GitHub repository devinilabs/pro-skill (24 stars, last pushed 26d ago), licensed MIT. It adds 88 tokens to every session and 2,195 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to thinking-orbs, differing in 0 lines, and is treated as a copy.
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