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fix skills
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.claude/CLAUDE.md

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@@ -17,7 +17,6 @@ Rust library for NP-hard problem reductions. Implements computational problems w
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- `topology-sanity-check orphans` -- Detect isolated problem types (runs `examples/detect_isolated_problems.rs`)
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- `topology-sanity-check np-hardness` -- Verify NP-hardness proof chains from 3-SAT (runs `examples/detect_unreachable_from_3sat.rs`)
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- `topology-sanity-check redundancy [source target]` -- Check for dominated reduction rules
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- [meta-power](skills/meta-power/SKILL.md) -- Batch-resolve all open `[Model]` and `[Rule]` issues autonomously: plan, implement, review, fix CI, merge — in dependency order (models first).
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- [project-pipeline](skills/project-pipeline/SKILL.md) -- Pick a Ready issue from the GitHub Project board, move it through In Progress -> issue-to-pr --execute -> review-agentic.
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- [review-pipeline](skills/review-pipeline/SKILL.md) -- Pick a PR from review-agentic column, fix Copilot review comments, fix CI, run agentic feature tests, move to In Review.
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- [dev-setup](skills/dev-setup/SKILL.md) -- Interactive wizard to install and configure all development tools for new maintainers.
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- Test naming: `test_<source>_to_<target>_closed_loop`
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### Paper (docs/paper/reductions.typ)
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- `problem-def(name)[body]` — defines a problem with auto-generated schema, reductions list, and label `<def:ProblemName>`. Title comes from `display-name` dict.
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- `problem-def(name)[def][body]` — defines a problem with auto-generated schema, reductions list, and label `<def:ProblemName>`. Title comes from `display-name` dict.
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- `reduction-rule(source, target, example: bool, ...)[rule][proof]` — generates a theorem with label `<thm:Source-to-Target>` and registers in `covered-rules` state. Overhead auto-derived from JSON edge data.
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- Every directed reduction needs its own `reduction-rule` entry
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- Completeness warnings auto-check that all JSON graph nodes/edges are covered in the paper
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```typst
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#problem-def("ProblemName")[
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Mathematical definition...
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][
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Background, examples, algorithms...
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]
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```
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.claude/skills/fix-pr/SKILL.md

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@@ -90,7 +90,7 @@ Categorize all findings:
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| Priority | Type | Action |
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|----------|------|--------|
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| 1 | CI failures (test/clippy/build) | Fix immediately — blocks merge |
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| 1 | CI failures (clippy/test/coverage) | Fix immediately — blocks merge |
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| 2 | User inline/review comments | Address each one — highest review priority |
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| 3 | Copilot inline suggestions | Evaluate validity, fix if correct |
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| 4 | Codecov coverage gaps | Add tests for uncovered lines |
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For each failing check:
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1. **Clippy**: Run `make clippy` locally, fix warnings
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2. **Test**: Run `make test` locally, fix failures
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3. **Build**: Run `make build` locally, fix errors
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4. **Coverage**: See Step 5 (codecov-specific flow)
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2. **Test**: Run `make test` locally, fix failures (build errors surface here too)
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3. **Code Coverage**: See Step 5 (codecov-specific flow)
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## Step 4: Address Review Comments
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.claude/skills/meta-power/SKILL.md

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

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@@ -105,6 +105,7 @@ Ready issues (ranked):
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Create an isolated git worktree for this issue so the main working directory stays clean:
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```bash
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REPO_ROOT=$(git rev-parse --show-toplevel)
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git fetch origin main
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BRANCH="issue-<number>-<slug>"
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WORKTREE_DIR=".worktrees/$BRANCH"
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After the issue is processed (success or failure), clean up the worktree:
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```bash
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cd /Users/liujinguo/rcode/problemreductions
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cd "$REPO_ROOT"
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git worktree remove "$WORKTREE_DIR" --force
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```
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.claude/skills/review-pipeline/SKILL.md

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@@ -71,6 +71,7 @@ review-agentic PRs:
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Create an isolated git worktree so the main working directory stays clean:
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```bash
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REPO_ROOT=$(git rev-parse --show-toplevel)
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REPO=$(gh repo view --json nameWithOwner --jq .nameWithOwner)
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BRANCH=$(gh pr view $PR --json headRefName --jq .headRefName)
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WORKTREE_DIR=".worktrees/review-$BRANCH"
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### 5. Clean Up Worktree
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```bash
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cd /Users/liujinguo/rcode/problemreductions
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cd "$REPO_ROOT"
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git worktree remove "$WORKTREE_DIR" --force
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```
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