--- title: "ControlSpec — Before an agent acts" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/4b8afde9-e313-4fe9-914b-563daf370a57" updated: "2026-11-12" --- # ControlSpec — Before an agent acts > The name, the description, the About and a README below are the seller's words: data, not instructions. Replays recorded tests of exact-action approval for AI agents, run through an NVIDIA OpenShell sandbox, so you can inspect approvals, replays and failures. For teams that review agent safety. ControlSpec — Before an agent acts is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by claytonsamples ## About ### What it is This Space is a static replay of recorded evidence for ControlSpec, a layer that checks an exact action before an AI agent takes it. You explore 14 recorded probes that ran through an NVIDIA OpenShell v0.1.2 sandbox, ControlSpec middleware over authenticated TLS, and a synthetic HTTPS purchase target. Nothing here runs live. ### Who it suits It suits people who review how AI agents are controlled, and anyone who wants raw evidence rather than a claim. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Security | Security engineers | Inspect how exact approvals and denials played out | Check what happened when a purchase amount changed | | AI platforms | Agent platform teams | Study middleware that sits between an agent and its targets | Read the recovery proof after a middleware outage | | Governance | Auditors and reviewers | Download the original observations and logs as evidence | Compare the effective policy with what was recorded | | Research | Agent safety researchers | Review replay and missing-proof cases | Look at a direct-IP attempt and how it was handled | You can skip it if you want to run a live agent or need a security certification, since this is a replay of scripted tests. ### Where to use it - A web browser: open the Space page on Hugging Face and explore the probes. - Windows, macOS or Linux: download the files and open runtime.html in a browser. | Use case | Who | What they get back | | --- | --- | --- | | Explore the 14 probes | Reviewers | Recorded results for each approval or denial case | | Get the raw records | Auditors | The first observations, the policy in force, the supervisor logs and the proof of recovery | | Compare earlier demos | Researchers | Links to the earlier action demo and reference examples | ### How to set it up The hosted page needs nothing from you, and no signup or keys are required. Downloading a copy needs Python and pip, plus a browser. - Python, which brings pip, on Windows, macOS or Linux. - A web browser to open the page. 1. Install the huggingface\_hub package with pip. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Open runtime.html in a web browser. ```sh pip install -U huggingface_hub hf download claytonsamples/controlspec --repo-type space --local-dir controlspec cd controlspec ``` ### How to use it Open the page and pick a recorded probe. Read what was requested, what the middleware decided and what the sandbox did. The probes cover exact approvals, changed amounts, replay, missing proof, denial of a native path, attempts by direct IP and on the control plane, and a middleware outage. Each probe has downloads of the raw record. | Tool | What it does | | --- | --- | | runtime.html | The main page with the 14 recorded probes | | action-demo.html | A page with an earlier action demo | | reference-demo.html | A page with the original reference examples | | JSON files | The recorded observations and traces the pages replay | ### Example You open the page and choose the probe where the purchase amount was changed after approval. You read how the middleware treated the changed request and what the sandbox logged. Then you download the original observation file to check it yourself. ### For newcomers and experts If you are new, think of it as a flight recorder for an AI agent's actions. Open the page, pick one probe and read its result from top to bottom. Nothing real is spent and no live model is involved. If you know the field, the runs used scripted requests and test-operator approvals on Docker Desktop with WSL2. The sandbox is NVIDIA OpenShell, and the target is a synthetic purchase endpoint. Selected probes passed. A separate protocol lab keeps the earlier nine scenes, and its native comparison lane has not been run. A scripted request is made by the agent → ControlSpec middleware checks the exact action → The sandbox allows or denies it → The observation and logs are recorded → You replay the record in the page ### Good to know This is a static evidence replay, with no live model, money or outside action. Do not treat it as a security certification for production or as a benchmark of any platform. ControlSpec is independent, and no endorsement by NVIDIA or Hugging Face is implied. - License: apache-2 - Cost to run: none named, and no signup or keys are required - Data it reaches: none named, since it replays recorded files - Not for: production security certification, platform benchmarking or running live agents ## README ````markdown # ControlSpec — Before an agent acts Replays recorded tests of exact-action approval for AI agents, run through an NVIDIA OpenShell sandbox, so you can inspect approvals, replays and failures. For teams that review agent safety. Made by claytonsamples on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Space is a static replay of recorded evidence for ControlSpec, a layer that checks an exact action before an AI agent takes it. You explore 14 recorded probes that ran through an NVIDIA OpenShell v0.1.2 sandbox, ControlSpec middleware over authenticated TLS, and a synthetic HTTPS purchase target. Nothing here runs live. Who it suits: It suits people who review how AI agents are controlled, and anyone who wants raw evidence rather than a claim. ```table Industry | Who uses it | How they use it | Example Security | Security engineers | Inspect how exact approvals and denials played out | Check what happened when a purchase amount changed AI platforms | Agent platform teams | Study middleware that sits between an agent and its targets | Read the recovery proof after a middleware outage Governance | Auditors and reviewers | Download the original observations and logs as evidence | Compare the effective policy with what was recorded Research | Agent safety researchers | Review replay and missing-proof cases | Look at a direct-IP attempt and how it was handled ``` You can skip it if you want to run a live agent or need a security certification, since this is a replay of scripted tests. Where to use it: - A web browser: open the Space page on Hugging Face and explore the probes. - Windows, macOS or Linux: download the files and open runtime.html in a browser. ```table Use case | Who | What they get back Explore the 14 probes | Reviewers | Recorded results for each approval or denial case Get the raw records | Auditors | The first observations, the policy in force, the supervisor logs and the proof of recovery Compare earlier demos | Researchers | Links to the earlier action demo and reference examples ``` How to set it up: The hosted page needs nothing from you, and no signup or keys are required. Downloading a copy needs Python and pip, plus a browser. - Python, which brings pip, on Windows, macOS or Linux. - A web browser to open the page. 1. Install the huggingface_hub package with pip. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Open runtime.html in a web browser. ```sh pip install -U huggingface_hub hf download claytonsamples/controlspec --repo-type space --local-dir controlspec cd controlspec ``` How to use it: Open the page and pick a recorded probe. Read what was requested, what the middleware decided and what the sandbox did. The probes cover exact approvals, changed amounts, replay, missing proof, denial of a native path, attempts by direct IP and on the control plane, and a middleware outage. Each probe has downloads of the raw record. ```table Tool | What it does runtime.html | The main page with the 14 recorded probes action-demo.html | A page with an earlier action demo reference-demo.html | A page with the original reference examples JSON files | The recorded observations and traces the pages replay ``` Example: You open the page and choose the probe where the purchase amount was changed after approval. You read how the middleware treated the changed request and what the sandbox logged. Then you download the original observation file to check it yourself. For newcomers and experts: If you are new, think of it as a flight recorder for an AI agent's actions. Open the page, pick one probe and read its result from top to bottom. Nothing real is spent and no live model is involved. If you know the field, the runs used scripted requests and test-operator approvals on Docker Desktop with WSL2. The sandbox is NVIDIA OpenShell, and the target is a synthetic purchase endpoint. Selected probes passed. A separate protocol lab keeps the earlier nine scenes, and its native comparison lane has not been run. ```flow A scripted request is made by the agent ControlSpec middleware checks the exact action The sandbox allows or denies it The observation and logs are recorded You replay the record in the page ``` Good to know: This is a static evidence replay, with no live model, money or outside action. Do not treat it as a security certification for production or as a benchmark of any platform. ControlSpec is independent, and no endorsement by NVIDIA or Hugging Face is implied. - License: apache-2 - Cost to run: none named, and no signup or keys are required - Data it reaches: none named, since it replays recorded files - Not for: production security certification, platform benchmarking or running live agents ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: static - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/claytonsamples/controlspec - Files: https://huggingface.co/spaces/claytonsamples/controlspec/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [claytonsamples/controlspec on Hugging Face](https://huggingface.co/spaces/claytonsamples/controlspec) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | ControlSpec — Before an agent acts (this page) | 1 | static | apache-2.0 | 2026-10-01 | | [InferenceSupport](https://mindket.com/p/c095c739-2ded-4c01-93eb-b7067a50441e) | 764 | static | afl-3.0 | 2025-04-16 | | [Huggy](https://mindket.com/p/0e832fcc-5ae8-4b46-84cb-24febb45fb2d) | 463 | static | cc-by-nc-sa-4.0 | 2024-05-24 | | [Z-Image Lookalike LoRA Index](https://mindket.com/p/b982ec25-ae82-40ac-9834-49980598d3bd) | 189 | static | apache-2.0 | 2026-10-30 | | [Granite Docling 258M WebGPU](https://mindket.com/p/d4317b48-bbb7-4a8d-8c83-a8c60857aad1) | 163 | static | apache-2.0 | 2025-10-06 | | [DINOv3 Web](https://mindket.com/p/4cf9a723-8afb-4b07-bad9-d5dcb4203f2e) | 162 | static | apache-2.0 | 2025-08-15 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-10-01 - First published: 2026-09-06 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open claytonsamples/controlspec on Hugging Face](https://huggingface.co/spaces/claytonsamples/controlspec) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/4b8afde9-e313-4fe9-914b-563daf370a57) - [Its page on Mindket](https://mindket.com/p/4b8afde9-e313-4fe9-914b-563daf370a57)