Overview
ripwire helps coding agents navigate unfamiliar repositories by building a deterministic symbol map from a bounded, disclosed corpus. The series follows filtering and extraction, approximate graph resolution, structural versus task ranking, budgeted context serving, impact and test checks, guarded edits, caching, and evaluation. It shows how to use the tool as qualified starting evidence—not a complete semantic model or proof of a safe change.
Learning outcomes
- ripwire improves a coding agent’s first repository decisions by ranking structural and task-relevant evidence, not by replacing source reading.
- Its graph and retrieval results are useful approximations only when corpus boundaries, ambiguity, truncation, and provenance remain visible.
- Context serving should match the question: signatures and edges for orientation, bodies for narrowed behavior, and source or compiler evidence when semantics matter.
- Safer changes combine impact, uses, history, quality deltas, test evidence, and guarded writes, while final correctness remains with engineers and native tools.
Keywords
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PlansFAQ
What problem does ripwire solve for AI coding agents?
ripwire reduces the cost of orienting in an unfamiliar repository by ranking symbols and relationships, then disclosing what the index covered and omitted. It narrows the next read rather than replacing source understanding.
How does ripwire keep repository context trustworthy?
It keeps context trustworthy by making the observation boundary, resolution provenance, ambiguity, budgets, parser health, and cache state explicit. These disclosures distinguish a measured absence from an unknown or approximate result.
When should an agent use ripwire instead of grep?
Use ripwire when the repository or task is structurally unfamiliar and relationships, ranking, or bounded context matter. Use ordinary search or a known-file read when the location is already clear and the map’s fixed overhead would cost more.
Can ripwire prove that a code change is safe?
No. ripwire can expose likely impact, uses, test obligations, quality regressions, history, and guard a precise single-symbol write, but its name-based graph and coverage remain bounded. Source, compiler or language-server evidence, tests, runtime checks, and human review still decide correctness.