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Estimate hybrid human and agent work v1.0.0

Use this resource to estimate development work done by humans and AI agents

New

  • 448 downloads
  • 153 likes
  • 202 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install ai-assisted-effort-estimation

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent adapts its estimate to your working mode, human-only, hybrid or agent-first, using three-point PERT estimates with stated assumptions. It also sets up a calibration loop so that estimates improve as real results come in.

Mostly picked by

Updated November 2, 2026

Card for the “Estimate hybrid human and agent work” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: three-point estimation procedure
  • SKILL.md: examples, common pitfalls and related skills

Good fit for

  • Your sprints mix developers and AI agents
  • You need to size a backlog of tasks

Not for

    Tags

    • estimation
    • PERT
    • agents
    • sprint planning

    About

    You say

    “Estimate these ten tickets in hybrid mode, with PERT assumptions and a calibration margin.”

    Card for the “Estimate hybrid human and agent work” skill

    Skill published by Enreign under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to estimate development work done by humans and AI agents
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md4.5 KB

    Origin and licence

    Listed unmodified

    Author
    Enreign
    Source
    github.com/sickn33/agentic-awesome-skills/tree/e9809578fd426a284af017c5db99f8eb6628e6ca/skills/progressive-estimation
    Licence
    MIT

    Notice

    « progressive-estimation » (Enreign, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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