Direct answer
A coding assistant ecology should separate code generation from code evaluation. The generator proposes; tests, static analysis, type checks, benchmark suites, and human review dispose.
Component map
| Niche | Model or tool | Fitness metric |
|---|---|---|
| Intent parser | Small local classifier | Correct task type |
| Patch generator | Code-specialist model | Tests passed and diff quality |
| Type predictor | Narrow model or adapter | Exact type matches and downstream compile rate |
| Test proposer | Proposer caste | Valid failing tests found |
| Reviewer | Critic model plus static tools | Defects caught before merge |
| Release summarizer | Formatting model | Accurate human-readable change note |
Workflow
PROCEDURE code_assistant_task(issue, repository_snapshot)
intent <- ROUTE_CODE_INTENT(issue)
candidate_patch <- GENERATE_PATCH(intent, repository_snapshot)
proposed_tests <- GENERATE_TESTS(issue, candidate_patch)
results <- RUN_STATIC_AND_UNIT_TESTS(candidate_patch, proposed_tests)
review <- RUN_CODE_REVIEW_CRITIC(candidate_patch, results)
IF results.fail OR review.critical_findings
RETURN REPAIR_LOOP_PACKET(candidate_patch, results, review)
END IF
RETURN HUMAN_MERGE_REVIEW(candidate_patch, results, review)
END PROCEDUREBreeding rule
Never let a patch generator rewrite its own test harness without separate code-breeding review. The strongest coding ecology breeds generators, test proposers, reviewers, and routers under different evidence surfaces.
Source reports used for this guide
These reports are preserved verbatim in the site archive. The guide above is an editorial synthesis and may narrow, qualify, or reorganize claims from the source material.