Skip to content
Agentmart
Submit a tool

ado-effort-estimation

Estimate Azure Boards work with a mandatory clarifying-question gate and story-point guardrails.

Skill by imported-and-adapted-by-lucy-camilo

IndexedApache-2.0★ 19
Write a review

Chalk Labs

Need help deploying ado-effort-estimation?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/camiloandresgtruniandes-ado-effort-estimation

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Estimate Azure Boards work with a mandatory clarifying-question gate and story-point guardrails. Trigger: when the user asks for effort sizing or story-point estimation.

Use cases: cloud

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/ado-effort-estimation

What's inside

Skill name
ado-effort-estimation
Description
Estimate Azure Boards work with a mandatory clarifying-question gate and story-point guardrails. Trigger: when the user asks for effort sizing or story-point estimation.
License
Apache-2.0
Metadata
author: imported-and-adapted-by-lucy-camilo · version: 1.1
Instructions
43 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# ado-effort-estimation

## OpenClaw Usage Notes

- These ADO workflow skills complement SDD; they do not replace SDD phase approvals.
- Ask only for missing Azure DevOps context that cannot be safely discovered.
- Do not create/update Azure Boards items unless the user explicitly asks for that external write.
- Keep project-specific conventions in the repo or ADO project documentation, not in this generic skill.

## When to Use

Use when estimating User Story effort for Azure Boards.

## Rules

- Ask for `ProjectName` and Azure DevOps project link at the start of each session.
- Validate `ProjectName` against the project in the provided link before estimating.
- Ask clarifying questions before assigning points. Do not estimate before clarification is complete.
- Clarifying questions must cover at least: work scope, risk, dependencies, unknowns, and test effort.
- Use the story-point table below as the authoritative sizing guide.
- If required estimation context is missing, ask for missing information and hold the estimate.
- Preserve hard mapping rules: `8 -> Spark` and `13 -> Split`.

## Story Point Sizing Guide

| Story Points | Work | Risk | Dependencies | Unknowns | Explanation |
|-------------|------|------|--------------|----------|-------------|
| 0.5+ | Piece of cake | - | - | - | Trivial work with virtually no risk, dependencies, or uncertainty. |
| 1+ | No-brainer | - | - | - | Very small and straightforward task with low effort. |
| 2 | Some | Little | Could be | - | Small task with minor risk or dependency. |
| 3 | Much | Some | Some | Could be | Medium-sized task with noticeable effort and uncertainty. |
| 5 | A lot | Much | Many | Some | Large task with significant effort and coordination. |
| 8 | Huge | A lot | A lot | Many | Complex task. Run a Spark first to reduce uncertainty. |
| 13 | High | High | High | High | Too large for one story. Split into smaller stories. |

## Threshold Guidance

- 0.5 to 3: ready to build.
- 5: significant story; review carefully.
- 8: Spark required before committing implementation.
- 13: Split required before implementation.

From CamiloAndresGTRUniandes/lucy-ai, Apache-2.0.

More from CamiloAndresGTRUniandes/lucy-ai

Signals

Stars
19
Forks
2
Open issues
0
Last commit (this folder)
Jul 29, 2026 (3 months ago)
Last release
Jul 31, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
1.1
License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from imported-and-adapted-by-lucy-camilo

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get ado-effort-estimation running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying ado-effort-estimation?

CallGet help
Cite this page

ado-effort-estimation skill. Agent Mart. https://agentmart.dev/skills/camiloandresgtruniandes-ado-effort-estimation (last updated 2026-10-24)