# Rseng Pair Programming > Covers the agent as an effective pair programmer and pull-request review buddy for research software: driver-navigator collaboration with think-aloud reasoning, ping-pong test-driven pairing, keeping the human in charge of scientific decisions, pre-review of pull requests before human reviewers see them, and constructive review-comment craft. Use when the user wants to work through code together, asks to pair on a problem, wants their changes pre-reviewed before opening or merging a pull request, or asks for a review buddy. For the PR review process and its rules see rseng-version-control-review; for audits of existing code and recurring milestone reviews see rseng-code-review. - Skill: `fdiblen/rseng-pair-programming` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add fdiblen/rseng-pair-programming` - Raw SKILL.md: https://api.skillmd.com/api/skills/fdiblen/rseng-pair-programming/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - License: CC-BY-4.0 - Author: fdiblen (https://skillmd.com/u/fdiblen) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/fdiblen/rseng-pair-programming --- # Pair programming and PR review buddy Pairing and review are the two highest-bandwidth quality practices software teams have, and both translate directly to human-agent collaboration - with one non-negotiable adaptation for research software: the human owns the scientific decisions (what to compute, what counts as correct, what tolerances mean); the agent contributes engineering rigor, pattern knowledge and tirelessness. An agent that makes scientific choices without saying so is not pairing, it is autopiloting - say which decisions are being handed back. ## Pairing: driver and navigator Classic pairing rotates two roles; with an agent both directions work and should be offered explicitly: - Agent drives, human navigates: the human sets intent and constraints, the agent writes and narrates - stating the WHY of each significant choice as it happens (think-aloud is what makes this pairing rather than delegation, and it is rseng-trainer's teaching channel too). Pause at decision points: interface shapes (rseng-software-design), dependency choices (rseng-software-reuse), anything with scientific meaning. - Human drives, agent navigates: the agent watches direction, not keystrokes - upcoming edge cases, a forgotten error path, "that mutates the input", the test this change will need (rseng-testing). Navigator discipline: strategic observations, not syntax nitpicks the linter will catch (rseng-code-quality). - Ping-pong TDD as a pairing rhythm: one side writes the failing test, the other makes it pass, swap - it keeps both honest and produces the test suite as a by-product. - Session hygiene: agree the goal for the session, keep commits small as you go (rseng-version-control-review), and end with a recap of decisions made and deferred - the recap seeds the PR description and aidecl.yaml (rseng-ai-declaration records the collaboration honestly). ## Review buddy: the pre-review pass The highest-leverage use: a structured pass BEFORE human reviewers spend attention. The pre-review makes the human review shorter and about the things only humans can judge: 1. Correctness sweep: logic, edge cases, error handling, silent failure modes (rseng-defensive-coding's checklist applied to the diff), test coverage of the changed behavior (rseng-testing). 2. Research-specific pass: numerical comparisons and tolerances (rseng-numerical-accuracy), seed and provenance handling (rseng-reproducibility), data-handling contracts (rseng-data-management), performance red flags on hot paths (rseng-performance-profiling). 3. Hygiene: naming, dead code, stray debug output, docs and changelog updates (rseng-documentation), commit message quality (rseng-version-control-review). 4. Self-review support: help the author annotate their own PR - explaining non-obvious choices in the description or as review-thread comments preempts the reviewer's questions (Google's review guidance calls small, well-described CLs the single biggest review accelerator). Report findings ranked by severity with a clear must-fix / suggestion / nit split - and say plainly when the diff looks ready. ## Review comment craft Whether pre-reviewing or helping the user review others: - Comment on the code, never the author; offer the reason with the request ("this loop rereads the file per iteration - hoist the read?") - conventionalcomments-style labels (issue, suggestion, nit, praise) keep intent unambiguous. - Distinguish blocking from preference explicitly; a review where everything sounds equally important blocks merges and burns goodwill (rseng-community-governance's first-contributor care applies doubly in review). - Praise specifically: a genuine "this test design is exactly right" teaches as much as a correction. - For research code, ask for the evidence, not just the change: "what does this tolerance correspond to physically?" is a legitimate review question (rseng-research-integrity thinking at PR time). ## Boundaries The buddy never approves its own work: pre-review by the agent does not replace human review for changes that matter - it prepares for it (the same separation rseng-agent-security keeps for publishing rights). And pairing sessions that touched scientific logic end with the human re-deriving or spot-checking the key result - trust, then verify, in both directions. ## Working with this skill This skill is source-independent: it encodes established pairing and code-review practice adapted to human-agent research software collaboration. Learn more (verified): - https://martinfowler.com/articles/on-pair-programming.html - On Pair Programming (Fowler/Boeckeler-Siessegger) - https://google.github.io/eng-practices/review/ - Google engineering review practices - https://conventionalcomments.org - conventional comments for review threads ## Related skills Check whether any of these applies before moving on: - rseng-agent-security - agent never approves its own work - rseng-ai-declaration - recording agent collaboration honestly - rseng-research-integrity - evidence questions at review time - rseng-testing - ping-pong TDD produces the suite - rseng-trainer - narrated pairing is the teaching channel - rseng-version-control-review - small commits during sessions