neqsim-code-health git:20261107.9b24822A

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---
name: neqsim-code-health
description: "Assess NeqSim maintainability, technical debt, dependency boundaries, complexity hotspots, duplication and new static-analysis findings. Use for code-health triage, a maintenance backlog, or planning a bounded refactoring with evidence."
---

# Assess code health

Read `docs/development/CODE_HEALTH.md` for commands, baseline policy and limitations.
Use current source and the exact base/head revisions. Discover existing implementations
with `devtools/capability_search.py` before proposing new APIs.
In connector-only sessions, inspect current GitHub source and CI artifacts; mark
local checks unrun instead of assuming that a checkout or build tool is available.

1. Run `devtools/code_health.py --output <evidence.json>` with the selected Python
   executable. Inspect findings and measured file metrics, not just the exit code.
2. Generate and supply PMD and SpotBugs reports for a static-analysis assessment.
   Missing reports or analysis errors are failures. Distinguish unmeasured coverage
   and unavailable history from measured zero values.
3. Rank candidates using branch counts, size, import dependencies, duplicate-window
   candidates, bounded history and relevant regression evidence. Size/branch counts
   are proxies; overlapping duplicate windows are not a percentage of duplicated code.
4. Check open work before selecting a change. Keep one coherent maintenance PR and
   coordinate overlapping files with existing campaigns.
5. State the problem, extension point, public contracts, numerical/performance risk,
   test commands and acceptance criteria. Prefer one responsibility with known callers.
6. Hand implementation to `@refactor` with `neqsim-safe-refactoring`, then request
   independent `@code-review` using `neqsim-code-review`. Reuse `@neqsim-test`
   and `@documentation` for distinct test and documentation work.

Return a ranked, source-linked backlog and a bounded first task. Record exact checks,
exit results and unresolved evidence. Never refresh the baseline to make a failure pass;
propose each baseline change explicitly with a reason. Do not call discovery coverage
or a maintenance metric numerical qualification.