fallow-review

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Review AI-generated or human-written code changes with fallow's graph-grounded review brief. Subtracts deterministic concerns (unused code, complexity, duplication, styling) from the loop, ranks what to look at by blast radius and risk, and surfaces the few consequential structural decisions (new public-API contracts, coupling/boundary crossings, new dependencies) as framed judgment questions anchored to verifiable signals. Drives a closed agent-contract loop: fetch the walkthrough guide, return a judgment, and have fallow post-validate it against the live graph (hallucinated or stale judgments are rejected). Use when asked to review a PR, review a branch, review a diff, do a code review, or check changed code before merge.

Code & Development 121 stars 9 forks Updated today MIT

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Skill Content

# Fallow Review: graph-grounded code review `fallow review` turns a changeset into a deterministic, graph-derived review brief and an agent-contract loop. It answers "where do I look, and what calls actually need human taste?" rather than "will CI block this?" (that is `fallow audit`, which gates). `review` always exits 0, so it is safe to run regardless of verdict. The four jobs it does, in order: - **subtract**: dead code, complexity, duplication, and styling for the changed files are reported and kept OUT of the judgment loop, so attention is not spent on what a deterministic check already owns. - **focus**: changed-file units are ranked by a composite attention score (fan-in/out, risk zone, change shape) with a `review-here` / `not-prioritized` label and a full `deprioritized` escape-hatch list, so nothing is hidden. - **structure**: the decision surface lifts the handful of consequential STRUCTURAL decisions out of the diff and frames each as a judgment question, capped to a working-memory-sized set, each anchored to a `signal_id` fallow emitted. - **direct**: the walkthrough guide hands an agent a graph-derived digest, the review direction, a graph-snapshot pin, and the exact judgment schema to return. ## When to use - Reviewing a PR, branch, or diff (AI-generated or human-written) before merge. - After an agent has done work and removed the fallow findings it could; this surfaces what is left for human/agent taste. - Producing inline-reviewable judgments that can ...

Details

Author
fallow-rs
Repository
fallow-rs/fallow-skills
Created
5 months ago
Last Updated
today
Language
JavaScript
License
MIT

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