Borrowing it
Nothing to install: this file belongs to RiggdAI/uniqent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/RiggdAI/uniqent/main/CLAUDE.mdgit clone --depth 1 https://github.com/RiggdAI/uniqentWrote 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/instructions/riggdai/uniqent/claude-md)<a href="https://agentmods.dev/instructions/riggdai/uniqent/claude-md"><img src="https://agentmods.dev/badge/instructions/riggdai/uniqent/claude-md/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/instructions/riggdai/uniqent/claude-md"><img src="https://agentmods.dev/badge/instructions/riggdai/uniqent/claude-md.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 | $0.03170 | $0.03170 |
| Opus 5 | $0.01585 | $0.01585 |
| Sonnet 5 | $0.00634 | $0.00634 |
| Haiku 4.5 | $0.00317 | $0.00317 |
Grade A, and why
uniqent CLAUDE.md 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 9d 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
What Uniqent is
Uniqent is a complete, open-source platform for portable AI agents — an n8n-inspired
workflow to build, package, share, and install whole agent "brains." A user composes a brain
(persona, memory, skills, MCP servers, tools, automations, channels, runtime config) in a
local-first visual builder, Uniqent Studio, and exports it as a single signed .uniqent
bundle (a gzipped tar). Anyone can then install that bundle in one click into the agent
framework they run (OpenClaw, Hermes, Claude Code, …); a per-framework adapter translates
the canonical bundle into that framework's native layout.
Authoring from scratch in Studio is the primary path; capturing/exporting an existing agent is secondary. Uniqent is the builder + packager + translator + installer — NOT where the agent runs (that's the framework). Unlike n8n (which builds and exports its own workflows), Uniqent sits above the frameworks so one brain travels between all of them. The headline use case is institutional-knowledge continuity — keep a departing person's agent brain and hand it to the next hire (see project memory).
Open source: the spec is CC0 (LICENSE-SPEC), the code is Apache-2.0 (LICENSE).
Non-negotiable principles (these OVERRIDE convenience)
- Secrets never travel in a bundle. Bundles declare credential requirements; the installer resolves real secrets locally into the target framework's own credential store.
- Bundles install from a raw file or URL with zero dependency on a hosted registry. The registry is optional convenience, never required.
- Install is a translation, not a copy. One canonical format → per-adapter native output.
- Trust is first-class. Signing, a permission manifest, and a sandboxed dry-run ship in v1.
- Lossy is acceptable, silent loss is not. When a target can't hold something (e.g. memory
limits), truncate/transform AND report exactly what changed in the plan's
lossiness.
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.
- 9d ago First seen · 172 lines · 3,170 tokens per session scan A 35e662d27666
uniqent CLAUDE.md is an instructions file published in the GitHub repository RiggdAI/uniqent (15 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 3,170 tokens to every session, about $0.0158 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.
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