Skill detail
fit-pathway
Supports role expectations and career progression, potentially useful to data engineers but not a practice skill.
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SKILL.md
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--- name: fit-pathway description: > See what's expected at your level, configure agents to meet your organization's engineering standard, and make staffing decisions you can defend. Use when expectations are unclear and you need role definitions by discipline, track, and level. Use when agents follow generic practices instead of your standard. Use when you analyze career progression gaps. Use when you generate job definitions, interview questions, or a published engineering standard site. license: Apache-2.0 metadata: version: "0.3.2" author: forwardimpact --- # Pathway Package Pathway provides a web application, a CLI, and formatters for career progression, job definitions, and agent-profile generation. Two audiences use `fit-pathway` differently: | Audience | Goal | How they run it | | ----------------- | ----------------------------------------------------------------- | ----------------------------------------------- | | **Organizations** | Publish an agent-aligned engineering standard for their engineers | `npx fit-pathway build` in a standalone project | | **Engineers** | Explore jobs, skills, and career progression | `npx fit-pathway` installed in their project | ## When to Use **Understand what's expected at your level:** - Look up role expectations — `npx fit-pathway job <discipline> <level>` - Understand proficiency and autonomy at each level — `npx fit-pathway level <id>` - Analyze career progression gaps — `npx fit-pathway progress <discipline> <level> --compare=<target>` - Explore skills, behaviours, and drivers — `npx fit-pathway skill <id>`, `npx fit-pathway behaviour <id>` **Configure agents to meet your engineering standard:** - Generate agent configurations — `npx fit-pathway agent <discipline> --track=<track> --output=./agents` - Preview what an agent profile includes — `npx fit-pathway agent <discipline> --track=<track>` **Make staffing decisions you can defend:** - Generate or compare job definitions — `npx fit-pathway job <discipline> <level> --track=<track>` - Select interview questions for a role — `npx fit-pathway interview <discipline> <level>` **Publish and maintain your engineering standard:** - Set up a standard project — `npx fit-map init` - Build a static site — `npx fit-pathway build` - Preview changes — `npx fit-pathway dev` --- ## How It Works ### Job Derivation Pathway derives a job in real time from three inputs: **discipline**, **level**, and optionally **track**. For each skill in the discipline: 1. The skill's tier in the discipline — core, supporting, or broad 2. The level's base proficiency for that tier gives the initial value (e.g. "foundational" for core skills at J060) 3. Track modifiers shift proficiency up or down **per capability**. A platform track with `scale: +1` raises all skills in the scale capability by one level. A `delivery: -1` modifier lowers delivery skills 4. The level's maximum base proficiency caps positive modifiers. Pathway clamps results to the valid range (awareness → expert) Behaviours follow the same pattern. They take base maturity from the level. Pathway then stacks and clamps the discipline and track modifiers. Some capabilities take a positive track modifier but are not in the base discipline. Pathway adds their skills as broad-type "track-added" skills. ### Agent Derivation Agent profiles reuse job derivation with three additions: 1. **Reference level** — Pathway selects it automatically. It takes the first level where core skills reach "practitioner". If no level qualifies, it falls back to "working", then to the middle level 2. **Skill filter** — Pathway removes `isHumanOnly` skills (physical presence, emotional judgment) 3. **Skill focus** — Pathway limits the matrix to the most relevant skills per stage and sorts them by tier (core → supportingRead the full source on GitHub (opens external page)