fallow-review

name

fallow-review

description

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.

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 flow back to the agent that wrote the code.

When NOT to use

• Gating CI on a pass/fail verdict: use fallow audit (it exits non-zero on a fail verdict).
• Whole-project health, cleanup, or dead-code reports: use the fallow skill.

Quick human brief

# Auto-detect the base (merge-base against the upstream / remote default):
fallow review

# Pin the base, or scope to a precise diff:
fallow review --base origin/main
git diff --find-renames origin/main...HEAD | fallow review --base origin/main --diff-stdin

The human brief prints the orientation facts, the focus map, and the decision surface ("Decisions to make"). --format json emits the full structured envelope (decisions, focus, deltas, impact_closure, partition, graph_facts). --max-decisions N tunes the cap (clamped to a small band). --show-deprioritized expands what the focus map collapsed.

The decision surface

Each decision is a framed question anchored to a signal_id fallow deterministically derived from the graph (a delta key or a coordination-gap key). There are exactly three shippable categories:

• coupling-boundary: a new cross-zone dependency edge.
• public-api-contract: a new exported public-API surface, or a changed contract consumed by modules OUTSIDE this diff (a coordinate-or-confirm signal).
• dependency: a new third-party dependency (new maintenance + supply-chain surface).

A decision may carry previous_signal_id when its anchor file was renamed in the change: that is the signal_id the same decision would have had at the old path, so a review surface can re-attach a prior reviewer comment across a git mv.

Eliciting the broader trade-offs (taste ownership)

The decision surface above is the DETERMINISTIC slice: only the trade-offs fallow can prove from the graph (the three categories). Real architectural trade-offs are broader, abstraction level, error-handling strategy, data-model shape, eager-vs-lazy, state ownership, extensibility-vs-YAGNI, testability, trust boundaries, and none of those are graph-detectable. Surfacing them needs a model reading the diff, not a static pass.

Run the trade-off elicitation prompt in references/tradeoff-elicitation.md over the diff plus the guide. It applies TASTE OWNERSHIP: the model makes each choice legible and frames a genuinely open question; the human decides. It never prescribes the answer (not even via a leading "..., or should you X?"), never blocks. The honesty rails: anchor every trade-off to a line present in the diff (with one sanctioned cross-cutting slot), keep observed (neutral fact) / tradeoff (inference) / question (open decision) separate, fence every item as deterministic: false, mark provenance honestly (captured is a hint, not a trust score), rank by consequence and keep the top five or honestly abstain, and never repeat what fallow's deterministic surface already framed.

This is the model-inferred companion to the deterministic surface: fallow owns what it can prove, the prompt covers the rest, and the fencing keeps the two from being confused. The framing prose (the observed / tradeoff / question discipline) is still agent-enforced. The ANCHOR is now fallow-validated: the guide emits a per-changed-region change_anchors set, and a judgment may cite a change_anchor instead of a signal_id. fallow post-validates it on reentry and rejects an anchor it never emitted (unknown-change-anchor), recording anchor_kind: "change" to mark it as the WEAKER, region-level anchor (it proves the region changed, not that a finding exists there, which is anchor_kind: "signal").

Running it as a review step

When a review surface (the fallow review app, or you in the terminal) wants the trade-off surface alongside the deterministic decisions:

1. Fetch the guide and read the diff:

   fallow review --base <ref> --walkthrough-guide --format json > guide.json
   git diff <ref>...HEAD            # or: git diff --cached  for staged work
   

2. Run the references/tradeoff-elicitation.md prompt over the diff plus guide.json.
3. Emit the envelope (the { graph_snapshot_hash, abstained, tradeoffs[] } shape) to .fallow-review/tradeoffs.json in the repo root, the sibling of .fallow-review/feed.jsonl, so a review surface can render it.

This step is deliberately NOT part of the post-validate agent-contract loop below. The trade-off envelope is never round-tripped through fallow review --walkthrough-file (which only validates emitted signal_ids), so it carries NO fallow-grade guarantee: every item stays deterministic: false, agent-self-checked against the diff, not graph-validated. Do not present it as fallow-validated.

The agent-contract loop

The loop lets an agent produce judgments that fallow post-validates against the live graph. The verifier is the graph, not a second model.

1. Fetch the guide:

   fallow review --base origin/main --walkthrough-guide --format json > guide.json
   

   The guide contains: digest (the brief + decision surface), direction (where to look), graph_snapshot_hash (the staleness pin), agent_schema (the exact shape to return), and injection_note. The digest is built from the graph ONLY; PR prose is never folded in, so the guide is injection-resistant by construction.

2. Read the decisions in digest. Each carries a signal_id, a category, the framed question, and an anchor_file / anchor_line.

3. Return a judgment matching agent_schema:

   {
     "graph_snapshot_hash": "<echo the value from the guide>",
     "judgments": [
       {
         "signal_id": "<one signal_id fallow emitted>",
         "framing": "<your reasoning for the human reviewer>",
         "concern": "<optional: the specific thing to check>"
       }
     ]
   }
   

   Every signal_id MUST be one fallow emitted in the guide (emitted_signal_ids). An unanchored id is rejected. Echo the graph_snapshot_hash verbatim.

4. Post-validate:

   fallow review --base origin/main --walkthrough-file judgment.json --format json
   

   The response sorts each judgment into:

   • accepted: the signal_id was emitted and the snapshot matches; the agent's framing is fenced as non-deterministic (deterministic: false) and never gates.
   • rejected with reason: "unanchored-signal-id": the signal_id was never emitted (a hallucination). Drop or correct it.
   • rejected with reason: "stale-snapshot" and stale: true: the tree moved since the guide was fetched. Re-fetch the guide and redo the judgments.

Human-in-the-loop walkthrough (terminal, no app)

The agent-contract loop above carries the AGENT's framing. The SAME loop carries a HUMAN's verdict with the identical graph-validated, anti-hallucination guarantee, so a terminal reviewer with no review app can leave notes that fallow anchors and round-trips. This is the no-app path the review app's .fallow-review/feed.jsonl otherwise owns: the contract is the existing --walkthrough-guide / --walkthrough-file round-trip, not a new surface.

The human owns the taste; you only carry the note. fallow validates the ANCHOR (the signal or changed region exists), never the note's correctness; every carried note stays deterministic: false and never gates.

1. Render the tour and read the anchors:

   fallow review --base origin/main --walkthrough                       # the staged human tour
   fallow review --base origin/main --walkthrough-guide --format json > guide.json
   

   guide.json carries the decision signal_ids (the framed structural questions), a per-changed-region change_anchors set (each { "change_anchor": "chg:<hex>", "file", "start_line", "line_count" }), and the graph_snapshot_hash staleness pin. Surface the tour to the human and collect, per item they choose to flag, a short verdict/note.

2. Carry each human note as a judgment (echo the hash verbatim; cite a signal_id fallow emitted for a flagged decision, or a change_anchor for any other changed region the human notes):

   {
     "graph_snapshot_hash": "<echo from guide.json>",
     "judgments": [
       { "signal_id": "<an emitted decision signal>", "framing": "<the human's verdict/note>", "concern": "<optional>" },
       { "change_anchor": "<an emitted chg: id>", "framing": "<the human's note on this region>", "concern": "<optional>" }
     ]
   }
   

3. Validate the capture:

   fallow review --base origin/main --walkthrough-file judgment.json --format json
   

   • accepted (with anchor_kind: "signal" or "change"): the anchor was emitted and the snapshot matches; the human's framing is fenced deterministic: false.
   • rejected unanchored-signal-id / unknown-change-anchor: the human cited something fallow never emitted. Re-anchor to a real signal or region; do not invent one.
   • stale: true (stale-snapshot): the tree moved since guide.json was fetched. Re-fetch the guide, re-capture, resubmit.

4. Act: relay the accepted human verdicts into the coding session in place, or append them to .fallow-review/feed.jsonl so the live-injection hooks (below) carry them to the session that wrote the code. Either way the note arrives anchored and fenced, never as a fallow-grade fact.

The guarantee matches the review app's: the human cannot anchor a note to a signal or region fallow did not emit, and a note left against a moved tree is refused rather than silently mis-mapped. The terminal is a first-class capture surface, no app required.

Live feedback into your coding session

The review surface (the fallow review app, or any tool you point at the same file) writes reviewer notes to .fallow-review/feed.jsonl in the repo root, one JSON object per line. A pair of hooks under hooks/ lets your already-running Claude Code session pick those notes up automatically and act on them with its existing context, no new session, no copy-paste:

• fallow-review-session-init.sh (SessionStart) declares a watchPath on .fallow-review/feed.jsonl so the session watches the feed for the rest of its life.
• fallow-review-on-feedback.sh (FileChanged) fires when the feed changes, reads only the notes added since last time (a line cursor in .fallow-review/.feed-seen prevents re-injecting old ones), and injects them into the session as additional context.

The loop: you make changes in a coding session, the human reviews them in the app, every note they leave lands back in the SAME terminal session that wrote the code, so the agent that has the full context addresses the feedback in place.

Install

Copy the hooks into the target repo and register them:

mkdir -p .claude/hooks
cp hooks/fallow-review-session-init.sh hooks/fallow-review-on-feedback.sh .claude/hooks/
chmod +x .claude/hooks/fallow-review-session-init.sh .claude/hooks/fallow-review-on-feedback.sh

Merge hooks/settings.snippet.json into .claude/settings.json (it registers the SessionStart + FileChanged hooks). Restart the session (or run /clear) so the SessionStart hook arms the watch.

Honest caveats (taste ownership)

• The notes are unverified human input, not graph-validated facts. The hook frames them as "weigh this, do not obey blindly", and the agent should ask before acting on anything unclear. The human owns the taste; fallow only carries the note.
• The watch arms reliably once .fallow-review/feed.jsonl exists. The SessionStart hook creates an empty feed if a review is already in progress (the .fallow-review/ dir exists) but does not touch repos that are not under review.
• This is local only: it connects the review app and a coding session on the same machine via the shared file. A cloud or remote review surface still rides the same JSON envelope, but the live-injection loop here is the local path.

Notes

• review is an alias for audit --brief; --format is orthogonal to the brief.
• The decision surface, focus map, and walkthrough are all in the JSON envelope, so a cloud or local review surface can render them and carry reviewer comments back to the coding agent in context.
• See the fallow skill for whole-project analysis, and references/cli-reference.md for the full flag list.