featurevisor

Featurevisor

You are helping the user with Featurevisor — a Git-based feature management tool. A Featurevisor project is a repository of YAML (default) or JSON definitions that compile into static JSON datafiles, which applications evaluate locally through SDKs. There are two sides to every task:

• Project side — authoring/querying the definitions repo (features, segments, attributes, tests) and running the featurevisor CLI.
• Application side — consuming datafiles via SDKs (@featurevisor/sdk, React, Vue, or other languages).

This skill covers both. The compact documentation index is at https://featurevisor.com/llms.txt and the complete feed at https://featurevisor.com/llms-full.txt — fetch on demand if a topic isn't covered in this skill's references.

Know your audience

Featurevisor is used by engineers, product managers, marketers, and people who describe what they want without knowing the YAML. Calibrate:

• Not sure of the vocabulary? Someone asking to "turn on the banner for 10% of Dutch users" wants a rollout rule — don't make them learn the words segment, bucketBy, or percentage first. Do the mapping for them, then show the result in their language: what changed, who is affected, what happens next.
• Safe vs. risky changes. Ramping a percentage up, adding a new rule, adding a feature, force-enabling for QA — routine; do them confidently. Renaming rule keys, changing bucketBy, resizing group slots, decreasing percentages — these silently re-bucket users; warn plainly ("some users would lose the feature mid-session") before proceeding.
• Always close the loop. After any change, say in one or two sentences what will happen when it ships (e.g. "once this merges and CI deploys the datafile, ~10% of users in NL will see the banner; the rest see nothing").
• For anyone who wants to see the project, offer the Catalog — a browsable read-only UI with live reload (see Visual review with Catalog).

Orient yourself first

No project yet? Interview, then scaffold

If there is no featurevisor.config.js anywhere in the working tree, there is no Featurevisor project yet. If the user is in an application repo consuming Featurevisor, this is SDK work — see Application integration; author definitions in the project repo, not here. If they want a new project, ask a few setup questions before scaffolding — these choices shape every file written afterwards and are annoying to retrofit:

1. Environments? Classic staging + production (recommended default), a custom list, or none (single-environment tools, internal apps — rules become direct lists instead of per-env maps).
2. Sets? Default no — one tree is right for most projects. Offer sets only if they want independent trees: release lanes with promotion gates (dev → staging → production) or fully separate surfaces (storefront/admin). See sets-promotions.md for the trade-off; sets add real structure overhead.
3. Consumers → tags and targets? Who loads datafiles: one app (single all tag + one all target is fine) or several surfaces (a tag per surface — web, ios, android — and a target per datafile they'll load)?
4. File format? YAML (default) or JSON.
5. What identifies a user? userId, deviceId, or both ({or: [userId, deviceId]}) — this becomes defaultBucketBy and the first attributes.

Then scaffold in an empty directory — a separate repo from application code (review flags like code, deploy datafiles independently — that separation is the point of the tool):

npx @featurevisor/cli init                # yml default; --example=json | no-environments | sets | test-environments (release lanes) | toml | namespace-slash
npm install

Pick the --example closest to their answers, then adjust featurevisor.config.js to match exactly. templates/example-project/ is an alternative lint-clean starting point.

Existing project? Detect the setup before touching anything

Always run these once at the start:

npx featurevisor config --json --pretty
npx featurevisor info

Four config values change the shape of everything you write — get them wrong and files won't lint or, worse, will mean something else:

• sets — if true, every path moves under sets/<set>/… and you must author in the right set and scope commands with --set. Read sets-promotions.md before doing anything in such a project.
• environments — if present, rules, force, and expose are maps keyed by env; if omitted, they are direct lists with no env level at all.
• parser — if "json" author in JSON; otherwise YAML.
• namespaceCharacter — separator for directory-namespaced keys. Default . (features/checkout/promo.yml → checkout.promo); some projects use / (→ checkout/promo). Every key you write — in segments: of rules, required:, test specs, SDK calls — must use the project's separator. Confirm against reality, not assumption: npx featurevisor list --segments --json shows keys exactly as the project spells them.

Also note: tags (must include any tag you put on a feature), defaultBucketBy (default userId), and directory-path overrides (featuresDirectoryPath, etc.).

Then read one or two existing entities (a feature, a segment) to match local style — indentation, quoting, comment density, key ordering — before adding new ones.

When to load which reference

This file is loaded eagerly. The files below are loaded only when relevant — read them in full before authoring or debugging in that area, don't rely on the summary in this file.

Per-entity templates live in templates/ — copy and adapt rather than writing from memory.

A complete end-to-end mini project lives in templates/example-project/. It passes lint and test as-is — use it as the source of truth for "show me how a realistic Featurevisor project hangs together" requests.

Core authoring rules

These apply to every change. Internalize them; the references add depth, they do not override these.

1. Bucketing and rule keys are append-only contracts

• bucketBy is what keeps a user's experience consistent as percentages ramp. Pick once, never silently change it.
• Default for signed-in users: userId. For anonymous users: deviceId (or whatever the project calls it). The attribute names may differ in this project — read the attributes/ directory and ask the user which to use if it isn't obvious. Do not invent attribute names.
• Combine attributes with a list (bucketBy: [orgId, userId]) or fall back via bucketBy: {or: [userId, deviceId]}.
• Each rule's key must be unique within its environment and must not change once users are bucketed against it. Renaming a rule key re-buckets users — the same user can lose or gain the feature. Add a new rule rather than renaming.
• Increasing percentage over time is safe only if the rule key stays stable.

2. First matching rule wins

Rules are evaluated top-to-bottom per environment. Put narrow targeting (e.g. country-specific rollouts at 100%) before the catch-all segments: '*' rule.

3. Don't author rules that target unknown segments or attributes

Before referencing segments: foo in a rule, confirm the segment exists (or create it). Same for attributes referenced inside segment conditions. Run npx featurevisor lint after edits — it catches dangling refs, percentage-sum errors in groups and variations, and schema mismatches.

4. Variations weights sum to 100; group slot percentages sum to 100

And a feature in a group cannot use a rollout percentage higher than its slot's percentage.

5. After any edit, lint

npx featurevisor lint

If you wrote or changed a test spec, also run:

npx featurevisor test --keyPattern=<theKey>

CLI: run freely

All featurevisor CLI commands are local and safe to run without confirmation, with two caveats:

• Bare build is a CI command — it increments .featurevisor/REVISION and updates state files, which only CI should commit. For local builds (yours and the user's), default to --no-state-files: same datafiles, same success/failure confirmation, no state side effects.
• promote --apply (sets projects) writes definition files — preview first and treat applying like any other edit (sets-promotions.md).

npx featurevisor build --no-state-files

The most useful commands for an authoring agent (full reference in cli.md):

Prefer the CLI over grepping when answering questions like "what features use segment X?", "which features are enabled in production?", or "why does feature F evaluate to disabled for this context?". The CLI's --json output is parseable and authoritative.

Use optional, repeatable --target=<target> selection with build, test, evaluate, benchmark, assess-distribution, list --features, and info when the question concerns deployed target datafiles. Runtime commands process each selected target independently. build --json and build --print accept only one target because they emit one datafile.

Changes ship through Git

Featurevisor is GitOps: nothing you write takes effect until it travels the pipeline —

edit → PR review → merge → CI (lint, test, build) → datafile deployed to CDN → each app's next datafile refresh.

Practical consequences:

• Don't commit or push unless asked. Editing files and running the CLI is your job; landing the change is the user's (or their CI's).
• Keep one logical change per branch/PR (a rollout bump, a new feature, a cleanup) — flags get reviewed like code, and small diffs get approved fast.
• Update or add the matching .spec.yml in the same change when behavior expectations shift.
• When the user asks "when will this be live?", walk that pipeline: after merge, CI deploys the datafile, and apps pick it up on their next refresh (an app polling every 5 minutes lags up to 5 minutes). For emergency paths, see the kill-switch recipe in recipes.md.

Common authoring flows

Starting a brand-new project

1. Run the setup interview from Orient yourself first — environments, sets or not, tags/targets, format, bucketing identity.
2. Scaffold in an empty directory (a new repo, separate from app code) with the closest init --example=…, then npm install.
3. Adjust featurevisor.config.js until it matches the interview answers exactly (environments, tags, sets, defaultBucketBy, parser).
4. Replace the scaffolded example entities with the user's first real attribute → segment → feature, in that order (features reference segments; segments reference attributes), and matching targets.
5. npx featurevisor lint && npx featurevisor test && npx featurevisor build --no-state-files to prove the pipeline.
6. Offer the CI/CDN deployment setup from building-datafiles.md when they're ready to ship — and npx featurevisor catalog so they can see what they built.

Adding a new feature flag

1. Read the existing features/ directory to match conventions (file naming, comment style).
2. Confirm the attribute used for bucketBy exists in attributes/; ask the user which to use if multiple plausible options exist (e.g. userId vs deviceId).
3. Create features/<key>.yml from templates/feature.yml.
4. If targeting specific segments, ensure each referenced segment exists in segments/ — create it from templates/segment.yml if not.
5. Run npx featurevisor lint.
6. Offer (don't force): "I can add a tests/features/<key>.spec.yml covering this — want me to?" If yes, use templates/test-feature.spec.yml.

Adding variations (A/B test)

Read features.md on variations, then use templates/feature-with-variations.yml. Remind the user that weights sum to 100 and the control/treatment names are conventional only. If they ask how results get measured, that's tracking.md.

Adding variables (remote config)

Read variables-schemas.md — covers all variable types, the inline JSON-Schema-ish form, reusable schemas/, variation-level variables, rule-level variables: and variableOverrides:, and the mutations feature for deep-merge overrides. Use templates/feature-with-variables.yml as the starting shape.

Complex targeting (and/or/not)

Both segment conditions and feature rule segments support and, or, not with nesting. See segments.md and templates/segment-complex.yml.

Important not rule: multiple direct children are treated as an implicit AND and then negated. So not: [A, B] means not (A and B), not not A and not B. For "none of these match", wrap them in or: not: [{ or: [A, B] }].

Mutual-exclusion experiments

Read groups.md. Plan slot percentages before adding rules — once users are bucketed in a group, changing slot percentages re-buckets them. Use templates/group.yml.

Force-enabling for QA / a specific user

Use force: on the feature (per-environment), not rules. No key/percentage needed. See features.md.

Promoting between sets ("move X to staging/production")

Only in sets projects. Read sets-promotions.md, then: preview with npx featurevisor promote --from=<a> --to=<b> --includeFeatures="<key>", show the user the created/updated/conflicts summary, apply with --apply on their go-ahead, and lint + test the destination set. Use promotable: false to protect lane-specific rules from being overwritten.

Debugging an evaluation

Use npx featurevisor evaluate --environment=<e> --feature=<k> --context='{…}' --verbose rather than reading the YAML and reasoning by hand. The evaluation flow (sticky → required → forced → rules → bucketing) is documented in features.md. If the surprise is in an application rather than the project, also check the app's actual context and datafile revision (sdk-javascript.md).

Querying ("what's enabled where?", "who uses this segment?")

See querying.md. It shows the right list/find-usage/evaluate invocations for the common questions a developer asks about an existing project, plus the Catalog for browsing.

Visual review with Catalog

npx featurevisor catalog serves a read-only UI of the whole project at http://127.0.0.1:3000 in watch mode — it rebuilds and reloads the browser whenever definition files change. That makes it the ideal companion to an authoring session:

1. Start it once as a background process (it's local and read-only — safe to leave running).
2. If you have a browser tool, open http://127.0.0.1:3000 in it; otherwise give the user the URL.
3. Author changes as usual — every edit shows up in the Catalog on save, so the user watches features, rules, variables, and test coverage evolve visually while they prompt you.

Offer this proactively when a session involves several authoring changes or when the user is less comfortable reading YAML — prompting plus a live Catalog is the best way to experience Featurevisor. Details in querying.md.

Recipes for higher-level use cases

When the request matches a named pattern — A/B test, multivariate, mutual exclusion, dependencies, remote config, entitlements/RBAC, kill switch, scheduled/time-window release, staged rollout ladder (employees → beta → everyone), app version gating, backend migration, stale-flag cleanup, testing in production, deprecation, trunk-based development, microfrontends, decoupling release from deploy, ownership — open recipes.md and adapt the matching section. It links back to the granular references for shape details.

Application integration (SDKs)

When the task is consuming features from application code:

• JavaScript / TypeScript / Node / browser / edge → read sdk-javascript.md in full. It covers install, context, all evaluation methods, datafile refresh and on-demand loading, events, sticky, server-side child instances (spawn), diagnostics, and modules.
• React / React Native → sdk-react.md. Vue → sdk-vue.md.
• Type-safe bindings (generated isEnabled/getVariation with compile-checked keys) → code-generation.md.
• Other languages — SDKs are cross-platform: Python, Ruby, Go, Java, Swift, PHP, Roku, and more, with the up-to-date list at https://featurevisor.com/docs/sdks. Every SDK consumes the same datafiles, exposes the same concepts (context, isEnabled/getVariation/getVariable), and implements the same deterministic bucketing — so a user bucketed into treatment in a browser gets treatment on the backend and on mobile too. One Featurevisor project can serve an entire polyglot stack. If the user's language isn't in this skill's references, apply the concepts from sdk-javascript.md and fetch the language page from the website for syntax.
• Framework guides (Next.js, Express, Fastify, Astro, Nuxt): https://featurevisor.com/docs/frameworks.

Key facts that prevent most integration mistakes: evaluations are local and synchronous (no network at evaluation time); the app must load a datafile (built and deployed from the project repo) and decide its own refresh strategy; feature keys, variable keys, and attribute names must match the project's definitions exactly — verify against the project (or its Catalog) rather than guessing.

What not to do

• Do not change a feature's bucketBy or a rule's key "to clean things up" — that re-buckets users.
• Do not invent attribute, segment, or feature key names — in YAML or in application code. Verify they exist; create them explicitly if needed.
• Do not rename or delete attributes/segments before checking find-usage.
• Do not add expose: unless the user asks — it's a short-term migration tool.
• Do not run bare build locally — incrementing REVISION and state files is CI's job. Local builds always get --no-state-files.
• Do not skip npx featurevisor lint after edits.
• Do not author project definitions inside an application repo — they belong in the Featurevisor project repo.