Tensorpm Agentic Pm
ListedTensorPM Agentic PM automates project management tasks within TensorPM, streamlining workflows and boosting team productivity for efficient operations.
Install on your platform
tensorpm-agentic-pm. SKILL.md frontmatter is not valid YAML, so the skills CLI skips it.We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-20. We don't show a command we know will fail.
What we know about this skill
Publisher
neo552
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill failed 2 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.
No undeclared network calls: failed
Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: tensorpm.com.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
Hosts contacted
tensorpm.comundeclaredraw.githubusercontent.comsource hostgithub.comsource hostWhat it found (3 of 8)
- .claude-plugin/marketplace.json:5contacts tensorpm.com
"url": "https://tensorpm.com" - SKILL.md:24contacts tensorpm.com
curl -fL -o /tmp/TensorPM-macOS.dmg https://tensorpm.com/api/download/macos - SKILL.md:27contacts tensorpm.com
curl -fL -o ~/TensorPM.AppImage https://tensorpm.com/api/download/linux
No pipe-to-shell installers: failed
Runs code fetched at install time in 1 place.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
What it found
- README.md:66remote script piped into a shell
curl -fsSL https://raw.githubusercontent.com/Neo552/TensorPM/main/scripts/install.sh | bash
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
Pinned to a commit: passed
Scanned neo552/tensorpm-releases at e6872346ae.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- e6872346ae
- Manifest
- SKILL.md
- Scanned
- 10 files, 895 lines
- Copies in repo
- 2 — all of them scanned
About this skill
What it does
The tensorpm-agentic-pm skill enables AI agents to perform project management tasks. It can generate project plans, track progress against those plans, and identify potential risks or roadblocks. This skill aims to automate routine PM activities, freeing up human managers for more strategic work.
When to use it
- Project Planning: Quickly create initial project outlines and timelines when starting a new initiative.
- Progress Tracking: Regularly monitor task completion and overall project health against established plans.
- Risk Identification: Proactively identify potential issues that could impact the project's success.
- Resource Allocation: Assist in determining optimal resource allocation based on project tasks and dependencies.
Key capabilities
- Project plan generation
- Progress tracking
- Risk identification
- Automated reporting
Example prompts
- "Create a project plan for launching a new marketing campaign, including key milestones and deadlines."
- "Update the project progress report based on the latest task completion data."
- "Identify potential risks to the software development project and suggest mitigation strategies."
Tips & gotchas
The skill's effectiveness depends on providing clear and detailed information about the project scope and tasks. Initial plans may require refinement and human oversight to ensure accuracy and feasibility.