cuopt-skill-evolution: check for established tools before writing custom parsers

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: ramakrishnap-nv

AGENTS.md

@@ -8,7 +8,7 @@ AI agent skills for NVIDIA cuOpt optimization engine. Skills live in **`skills/`
 
 ### Rules
 - `skills/cuopt-user-rules/` — Base rules for end users calling cuOpt (routing, LP, MILP, QP, install, server). Not for cuOpt internals — see `skills/cuopt-developer/`. Read first for user-facing tasks; choose skills from the index below by task and interface.
-- `skills/cuopt-developer/` — Modify, build, test, debug, and contribute to cuOpt internals (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions. **Also read for any CI or workflow change** (new jobs, new scripts, dependency additions) — the existing pipeline in `ci/`, `pr.yaml`, and `build.yaml` must be understood before adding anything new. For **VRP dimension** work (combine invariants, fwd/bwd propagation, new constraints/objectives in the routing engine), read **`skills/cuopt-developer/references/vrp_skills.md`** in addition to `SKILL.md`.
+- `skills/cuopt-developer/` — Modify, build, test, debug, and contribute to cuOpt internals (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions. **Also read for any CI or workflow change** (new jobs, new scripts, dependency additions) — the existing pipeline in `ci/`, `pr.yaml`, and `build.yaml` must be understood before adding anything new. **Before writing a custom script to extract, parse, or transform content, check whether an established tool already exists** (e.g. numpydoc for Python docstrings, Doxygen for C/C++ headers, pandoc for markup conversion) — custom parsers are a last resort. For **VRP dimension** work (combine invariants, fwd/bwd propagation, new constraints/objectives in the routing engine), read **`skills/cuopt-developer/references/vrp_skills.md`** in addition to `SKILL.md`.
 - `skills/cuopt-skill-evolution/` — Skill evolution: after solving a non-trivial problem, propose skill updates to capture generalizable learnings.
 
 ### Common (concepts only; no API code)