Favoritable Laravel Package

Product Decisions This Supports

• Feature enablement for engagement loops. A polymorphic "favoritable" trait is the substrate for likes, bookmarks, saves, watchlists, "add to favorites," and lightweight social proof counters. If any of these are on the roadmap, this package collapses a multi-sprint build into an integration task.
• Build vs. buy (build vs. adopt). Typical in-house cost for favorites is 1–3 weeks of engineering plus ongoing ownership of migrations, polymorphic relations, uniqueness/duplicate-prevention, counter caching, and cascade deletes. This is a well-bounded, low-differentiation domain — a strong candidate for adoption rather than building, freeing capacity for the differentiators.
• Prioritization and sequencing. Because integration cost is low, engagement features can be scheduled late and still ship in-cycle. Useful when debating whether a "social proof" epic deserves a full quarter or a single iteration.
• Metrics and instrumentation planning. Favorites generate first-party intent signals (saves are typically a stronger intent signal than likes). This informs decisions about what to log, whether to power "recently saved" surfaces, and whether downstream ranking/recommendation work is justified by the data volume this produces.
• Scope control on adjacent requests. Once favorites exist, expect follow-on asks (per-user privacy, favorite counts on cards, notifications on being favorited, exporting saved items). Deciding up front which of these are in-scope prevents the package from becoming an unplanned platform commitment.
• v1.0.0 as a semver signal. A 1.0.0 tag is a maturity claim: the maintainers are asserting API stability and a breaking-change policy. That is a meaningful input to "can we depend on this in production," though the release notes themselves are empty beyond a changelog link — so the claim is unverified by the notes and needs independent diligence.

When to Consider This Package

Consider it when:

• The requirement is a conventional boolean or single-type favorite/bookmark on one or more Eloquent models, and you want polymorphic support (favoriting Post, Comment, Product) without hand-rolling morph tables.
• Your team is Laravel-idiomatic and values a trait-plus-migration integration over a bespoke service.
• You need the 80% case — attach/detach/toggle, per-user uniqueness, retrieval of a user's favorites, counts — and are comfortable extending it for the rest.
• You want to de-risk the schedule: a small surface area means a failed adoption is cheap to reverse, and lock-in is low because the data model (a favorites table with morph columns) is trivially portable.
• You are validating demand for engagement features and want a cheap instrument rather than a platform bet.

Look elsewhere (or build) when:

• You need typed reactions (emoji sets, multiple reaction kinds), weighted signals, or reaction-level aggregation — that is a different data model and usually a different package or a custom build.
• You need feed ranking, recommendations, or a social graph. Favorites are an input to those systems; this package is not the system.
• Write volume is very high (millions of favorites/day) and you need partitioned tables, async counter reconciliation, or a dedicated store. An Eloquent trait will meet the functional spec and miss the operational one.
• You need per-record privacy rules, audit trails, moderation, or GDPR-grade deletion guarantees as first-class features rather than things you bolt on.
• Maintenance signals are weak. A 1.0.0 tag with release notes that contain only a changelog URL is not evidence of an active maintainer, a security policy, or test coverage. Single-maintainer packages in the critical path warrant a fork-and-own contingency or a hard pass.
• You need vendor support, an SLA, or a compliance attestation.

Diligence to run before committing (release notes are insufficient): review the changelog and diff for the 0.x → 1.0.0 boundary, confirm test suite and CI status, check issue/PR responsiveness and last-commit recency, confirm published security policy, verify the migration's index and uniqueness constraints, and read the trait for N+1 query behavior on count/isFavorited checks.

How to Pitch It (Stakeholders)

For executives (one paragraph): We are evaluating a small open-source Laravel package that provides "favoriting" — likes, bookmarks, saves — as a reusable component rather than something we build. The commercial case is straightforward: this is undifferentiated plumbing that would otherwise cost one to three engineer-weeks plus permanent maintenance, and it unblocks a family of engagement features we can then sequence on our own terms. The package just reached v1.0.0, which is the maintainers' signal that the API is now stable; that matters for production dependency. The risk is proportionate and bounded — the data model is a simple table we could reproduce in-house, so lock-in is low and reversal is cheap. What I am not claiming is that v1.0.0 is a quality audit: the release notes contain only a changelog link, so I am asking for a short diligence pass (test coverage, maintainer activity, security policy, query behavior) before we put it in the critical path. Recommendation: adopt provisionally for the engagement epic, with a named owner and a fallback of a ~1-week in-house build if diligence fails.

For engineering (what you're actually signing up for): A trait you apply to user and target models, a published migration, and a small API surface around attach/detach/toggle, uniqueness enforcement, and count retrieval. Integration is hours, not days. Two things to verify rather than assume: (1) the polymorphic indexes in the shipped migration — confirm the unique constraint is on (user_id, favoritable_type, favoritable_id) and that count queries are not causing N+1s on list views; (2) the 0.x → 1.0.0 diff — semver says the public API is now frozen, but with no narrative in the release notes we should confirm nothing was renamed or dropped that we'd have depended on. Treat the dependency as forkable: vendor it or pin the tag so an abandoned upstream doesn't block us. If typed reactions or high-volume writes are on the horizon, flag it now — that changes the build-vs-adopt answer.