Refactor generated doc exports and remove centralized trait tests (#676)

* initial

* clean up reduction_graph.json

* refactor-remove-conflicting files

* update skills and prompts

* relax model test naming to flexible coverage with >= 3 test floor

Replace rigid per-model test function name checklist with flexible
coverage guidance enforced by a minimum of 3 test functions. All three
files (CLAUDE.md, add-model skill, structural reviewer) are now
consistent on the threshold.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* remove conflicting generated files

These files were intentionally removed earlier in this branch;
re-delete after merge conflict resolution.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: GiggleLiu

.claude/CLAUDE.md

@@ -207,7 +207,7 @@ New code must have >95% test coverage. Run `make coverage` to check.
 ### Naming
 
 - Reduction tests: `test_<source>_to_<target>_closed_loop`
-- Model tests: `test_<model>_basic`, `test_<model>_serialization`
+- Model tests: descriptive names — e.g., `test_<model>_creation`, `test_<model>_evaluate_*`, `test_<model>_direction`, `test_<model>_solver`, `test_<model>_serialization`. Use whichever are relevant; there is no fixed per-model naming set.
 - Solver tests: `test_<solver>_<problem>`
 
 ### Key Testing Patterns
@@ -218,6 +218,8 @@ See Key Patterns above for solver API signatures. Follow the reference files for
 
 Unit tests in `src/unit_tests/` linked via `#[path]` (see Core Modules above). Integration tests in `tests/suites/`, consolidated through `tests/main.rs`. Canonical example-db coverage lives in `src/unit_tests/example_db.rs`.
 
+Model review automation checks for a dedicated test file under `src/unit_tests/models/...` with at least 3 test functions. The exact split of coverage is judged per model during review.
+
 ## Documentation Locations
 - `README.md` — Project overview and quickstart
 - `.claude/` — Claude Code instructions and skills
@@ -258,7 +260,7 @@ Also add to the `display-name` dictionary:
 ]
 ```
 
-Every directed reduction in the graph needs its own `reduction-rule` entry. The paper auto-checks completeness against `reduction_graph.json`.
+Every directed reduction in the graph needs its own `reduction-rule` entry. The paper auto-checks completeness against the generated `reduction_graph.json` export.
 
 ## Complexity Verification Requirements
 

.claude/skills/add-model/SKILL.md

@@ -75,7 +75,6 @@ Before implementing, make sure the plan explicitly covers these items that struc
 - CLI discovery and `pred create <ProblemName>` support are included where applicable
 - A canonical model example is registered for example-db / `pred create --example`
 - `docs/paper/reductions.typ` adds both the display-name dictionary entry and the `problem-def(...)`
-- `src/unit_tests/trait_consistency.rs` is updated
 
 ## Step 1: Determine the category
 
@@ -196,32 +195,24 @@ This example is now the canonical source for:
 
 Create `src/unit_tests/models/<category>/<name>.rs`:
 
-Required tests:
-- `test_<name>_creation` -- construct an instance, verify dimensions
-- `test_<name>_evaluation` -- verify `evaluate()` on valid and invalid configs
-- `test_<name>_direction` -- verify optimization direction (if optimization problem)
-- `test_<name>_serialization` -- round-trip serde test (optional but recommended)
-- `test_<name>_solver` -- verify brute-force solver finds correct solutions
-- `test_<name>_paper_example` -- **use the same instance from the paper example** (Step 6), verify the issue's expected outcome is valid/optimal and the solution count matches
+Every model needs **at least 3 test functions** (the structural reviewer enforces this). Choose from the coverage areas below — pick whichever are relevant to the model:
 
-The `test_<name>_paper_example` test is critical for consistency between code and paper. It must:
-1. Construct the exact same instance shown in the paper's example figure
+- **Creation/basic** — exercise constructor inputs, key accessors, `dims()` / `num_variables()`.
+- **Evaluation** — valid and invalid configs so the feasibility boundary is explicit.
+- **Direction** — verify optimization direction (optimization problems only).
+- **Solver** — brute-force solver finds correct solutions (when the model is small enough).
+- **Serialization** — round-trip serde (when the model is used in CLI/example-db flows).
+- **Paper example** — verify the worked example from the paper entry (see below).
+
+When you add `test_<name>_paper_example`, it should:
+1. Construct the same instance shown in the paper's example figure
 2. Evaluate the solution from the issue's **Expected Outcome** section as shown in the paper and assert it is valid (and optimal for optimization problems)
-3. Use `BruteForce` to find all optimal/satisfying solutions and assert the count matches the paper's claim
+3. Use `BruteForce` to confirm the claimed optimum/satisfying solution count when the instance is small enough for unit tests
 
-This test should be written **after** Step 6 (paper entry), once the example instance and expected outcome are finalized. If writing tests before the paper, use the issue's Example Instance + Expected Outcome as the source of truth and come back to verify consistency.
+This test is usually written **after** Step 6 (paper entry), once the example instance and expected outcome are finalized. If writing tests before the paper, use the issue's Example Instance + Expected Outcome as the source of truth and come back to verify consistency.
 
 Link the test file via `#[cfg(test)] #[path = "..."] mod tests;` at the bottom of the model file.
 
-## Step 5.5: Add trait_consistency entry
-
-Add the new problem to `src/unit_tests/trait_consistency.rs`:
-
-1. **`test_all_problems_implement_trait_correctly`** — add a `check_problem_trait(...)` call with a small instance
-2. **`test_direction`** (optimization problems only) — add an `assert_eq!(...direction(), Direction::Minimize/Maximize)` entry
-
-This is **required** for every new model — it ensures the Problem trait implementation is well-formed.
-
 ## Step 6: Document in paper
 
 Write a `problem-def` entry in `docs/paper/reductions.typ`. **Reference example:** search for `problem-def("MaximumIndependentSet")` to see the gold-standard entry — use it as a template.
@@ -294,5 +285,4 @@ If running standalone (not inside `make run-plan`), invoke [review-implementatio
 | Missing from CLI help table | Must add entry to "Flags by problem type" table in `cli.rs` `after_help` |
 | Schema lists derived fields | Schema should list constructor params, not internal fields (e.g., `matrix, k` not `matrix, m, n, k`) |
 | Missing canonical model example | Add a builder in `src/example_db/model_builders.rs` and keep it aligned with paper/example workflows |
-| Forgetting trait_consistency | Must add entry in `test_all_problems_implement_trait_correctly` (and `test_direction` for optimization) in `src/unit_tests/trait_consistency.rs` |
 | Paper example not tested | Must include `test_<name>_paper_example` that verifies the exact instance, solution, and solution count shown in the paper |

.claude/skills/add-rule/SKILL.md

@@ -170,8 +170,8 @@ Checklist: notation self-contained, complexity cited, overhead consistent, examp
 ## Step 6: Regenerate exports and verify
 
 ```bash
-cargo run --example export_graph    # Update reduction_graph.json
-cargo run --example export_schemas  # Update problem schemas
+cargo run --example export_graph    # Generate reduction_graph.json for docs/paper builds
+cargo run --example export_schemas  # Generate problem schemas for docs/paper builds
 make test clippy                    # Must pass
 ```
 

.claude/skills/final-review/SKILL.md

@@ -184,7 +184,6 @@ Verify the PR includes all required components. Check:
 - [ ] Canonical model example function in the model file
 - [ ] Paper section in `docs/paper/reductions.typ` (`problem-def` entry)
 - [ ] `display-name` entry in paper
-- [ ] `trait_consistency.rs` entry in `src/unit_tests/trait_consistency.rs` (`test_all_problems_implement_trait_correctly`, plus `test_direction` for optimization)
 - [ ] Aliases: if provided, verify they are standard literature abbreviations (not made up); if empty, confirm no well-known abbreviation is missing; check no conflict with existing aliases
 
 **For [Rule] PRs:**

.claude/skills/issue-to-pr/SKILL.md

@@ -97,7 +97,7 @@ The plan MUST reference the appropriate implementation skill and follow its step
 Include the concrete details from the issue (problem definition, reduction algorithm, example, etc.) mapped onto each step.
 
 **Plan batching:** The paper writing step (add-model Step 6 / add-rule Step 5) MUST be in a **separate batch** from the implementation steps, so it gets its own subagent with fresh context. It depends on the implementation being complete (needs exports). Example batch structure for a `[Model]` plan:
-- Batch 1: Steps 1-5.5 (implement model, register, CLI, tests, trait_consistency)
+- Batch 1: Steps 1-5.5 (implement model, register, CLI, tests)
 - Batch 2: Step 6 (write paper entry — depends on batch 1 for exports)
 
 **Solver rules:**
@@ -223,12 +223,11 @@ EOF
 python3 scripts/pipeline_pr.py comment --repo "$REPO" --pr "$PR" --body-file "$COMMENT_FILE"
 rm -f "$COMMENT_FILE"
 
-# Repo verification may regenerate tracked exports (notably after `make paper`).
+# Repo verification may regenerate ignored doc exports (notably after `make paper`).
 # Inspect the tree once more before pushing.
 git status --short
 
-# If expected generated exports changed, stage them before push.
-git add docs/src/reductions/problem_schemas.json docs/src/reductions/reduction_graph.json
+# Generated doc exports under docs/src/reductions/ are ignored; do not stage them.
 
 # The issue plan file must be gone before push.
 test ! -e docs/plans/<plan-file>.md

.claude/skills/review-implementation/structural-reviewer-prompt.md

@@ -33,17 +33,15 @@ Given: problem name `P` = `{PROBLEM_NAME}`, category `C` = `{CATEGORY}`, file st
 | 5 | `OptimizationProblem` or `SatisfactionProblem` impl | `Grep("(OptimizationProblem|SatisfactionProblem).*for.*{P}", file)` |
 | 6 | `#[cfg(test)]` + `#[path = "..."]` test link | `Grep("#\\[path =", file)` |
 | 7 | Test file exists | `Glob("src/unit_tests/models/{C}/{F}.rs")` |
-| 8 | Test has creation test | `Grep("fn test_.*creation|fn test_{F}.*basic", test_file)` |
-| 9 | Test has evaluation test | `Grep("fn test_.*evaluat", test_file)` |
-| 10 | Registered in `{C}/mod.rs` | `Grep("mod {F}", "src/models/{C}/mod.rs")` |
-| 11 | Re-exported in `models/mod.rs` | `Grep("{P}", "src/models/mod.rs")` |
-| 12 | `declare_variants!` entry exists | `Grep("declare_variants!|default opt|default sat|opt {P}|sat {P}", file)` |
-| 13 | CLI `resolve_alias` entry | `Grep("{P}", "problemreductions-cli/src/problem_name.rs")` |
-| 14 | CLI `create` support | `Grep('"{P}"', "problemreductions-cli/src/commands/create.rs")` |
-| 15 | Canonical model example registered | `Grep("{P}", "src/example_db/model_builders.rs")` |
-| 16 | Paper `display-name` entry | `Grep('"{P}"', "docs/paper/reductions.typ")` |
-| 17 | Paper `problem-def` block | `Grep('problem-def.*"{P}"', "docs/paper/reductions.typ")` |
-| 18 | `trait_consistency` entry | `Grep("{P}", "src/unit_tests/trait_consistency.rs")` |
+| 8 | Test file has >= 3 test functions | `Grep("fn test_", test_file)` — count matches, FAIL if < 3 |
+| 9 | Registered in `{C}/mod.rs` | `Grep("mod {F}", "src/models/{C}/mod.rs")` |
+| 10 | Re-exported in `models/mod.rs` | `Grep("{P}", "src/models/mod.rs")` |
+| 11 | `declare_variants!` entry exists | `Grep("declare_variants!|default opt|default sat|opt {P}|sat {P}", file)` |
+| 12 | CLI `resolve_alias` entry | `Grep("{P}", "problemreductions-cli/src/problem_name.rs")` |
+| 13 | CLI `create` support | `Grep('"{P}"', "problemreductions-cli/src/commands/create.rs")` |
+| 14 | Canonical model example registered | `Grep("{P}", "src/example_db/model_builders.rs")` |
+| 15 | Paper `display-name` entry | `Grep('"{P}"', "docs/paper/reductions.typ")` |
+| 16 | Paper `problem-def` block | `Grep('problem-def.*"{P}"', "docs/paper/reductions.typ")` |
 
 ## Rule Checklist
 

.claude/skills/review-pipeline/SKILL.md

@@ -329,7 +329,7 @@ Completed: 2/2 | All moved to Final review
 | Guessing on an issue card with multiple linked repo PRs | Stop, show options to the user, and recommend the most likely correct OPEN PR |
 | Picking a PR before Copilot has reviewed | Inspect the checked-out diff and PR body first. If the PR is incomplete, comment and move it back to Ready. If it is review-ready, request Copilot review and switch to another item instead of waiting |
 | Missing project scopes | Run `gh auth refresh -s read:project,project` |
-| Skipping review-implementation | Always run structural completeness check in Step 2b — it catches gaps Copilot misses (paper entries, CLI registration, trait_consistency) |
+| Skipping review-implementation | Always run structural completeness check in Step 2b — it catches gaps Copilot misses (paper entries, CLI registration, example-db wiring) |
 | Skipping agentic tests | Always run test-feature even if CI is green |
 | Not checking out the right branch | Use `gh pr view` to get the exact branch name |
 | Waiting idle for Copilot | Request the review, leave the PR in Review pool, and keep triaging other items in the same run |

docs/src/design.md

@@ -230,7 +230,8 @@ Exported files:
 - [reduction_graph.json](reductions/reduction_graph.json) — all problem variants and reduction edges
 - [problem_schemas.json](reductions/problem_schemas.json) — field definitions for each problem type
 
-Regenerate with `cargo run --example export_graph` and `cargo run --example export_schemas`.
+These JSON assets are generated during `make doc`, `make mdbook`, and `make paper`; they are build artifacts, not committed source files.
+Generate them manually with `cargo run --example export_graph` and `cargo run --example export_schemas` when you need the raw exports locally.
 
 ### Path finding
 

docs/src/getting-started.md

@@ -207,6 +207,7 @@ problemreductions = { version = "0.2", default-features = false }
 
 The library exports machine-readable metadata useful for tooling and research:
 
+These files are generated when you build the docs locally.
 - [reduction_graph.json](reductions/reduction_graph.json) lists all problem variants and reduction edges
 - [problem_schemas.json](reductions/problem_schemas.json) lists field definitions for each problem type