agentleFS
flightctlflightctl/ai-workflows/sizing/SKILL.md

sizing

Skill10 starsChanged 21 days agoMITView on GitHub

Pre-cycle Feature sizing workflow that assesses Features from Jira using T-shirt sizes (XS–XXL), produces per-team effort breakdowns (DEV, QE, UX, UI, DOCS), and writes results back to Jira. Accepts a single Feature or all Features in a Fix Version for batch sizing. Use when sizing Features for cycle planning, prioritizing a release backlog, or evaluating whether a Feature fits in a cycle. Activated by commands: /ingest, /assess, /apply.

2 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If the user invoked a specific command (e.g., /assess, /apply), read commands/{command}.md and follow it.

    line 17
  2. Distinctive:

    If a step fails or produces unexpected output (e.g., Jira MCP errors, network failures, invalid issue keys), stop and report the error to …

    line 22

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Sizing Workflow Orchestrator

Quick Start

  1. If the user invoked a specific command (e.g., /assess, /apply), read commands/{command}.md and follow it.
  2. Otherwise, read skills/controller.md to discover the input and route it through the phase dispatcher.

If a step fails or produces unexpected output (e.g., Jira MCP errors, network failures, invalid issue keys), stop and report the error to the user. Do not advance to the next phase. Offer to retry the failed step or escalate.

For principles, hard limits, safety, quality, and escalation rules, see guidelines.md. The scripts/ helpers compact source data, validate AI judgments, calculate derived values, and render artifacts; use JSON artifacts between phases.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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