--- name: review-scoring-f8ea5c4a9e66 description: The refutation-based review rubric used by the refutation-reviewer agent and the Write-Review-Fix-Confirm (WRFC) workflow template. A defect list with severity, not a single pass/fail score. Load when reviewing a change or deciding whether a review's findings clear the bar to merge. --- # review-scoring v1's review rubric was a single scalar score (0-10, threshold 9.9) computed by an automated runtime daemon. That daemon is cut for v2 (no standing usage justified keeping a background process for it) and the scalar-score design itself didn't survive review: a single number hides which specific claims were checked and which weren't. v2's rubric is a **defect list with severity**, produced by a human-in-the-loop review (the refutation-reviewer agent, or you reviewing your own or another agent's work). This skill is that rubric. ## The rubric A review is not "does this look right." It's "what would prove this wrong, and did I check for it." For the change under review: 1. **List the claims.** What does the implementer say the change does? (Handles the empty-input case. Covered by a test. Matches the existing error-handling pattern. Doesn't leak the new field to unauthorized users.) 2. **Try to falsify each one.** For each claim, find the concrete input, state, or code path that would make it false. Actually trace it or run it, don't just judge plausibility. 3. **Record what survived and what didn't**, each with: - **File/line.** Where the defect is, precisely. - **Failure scenario.** The concrete input/state that triggers wrong output, a crash, or data loss. "This looks fragile" is not a failure scenario; "calling this with an empty array throws because `arr[0]` is accessed unconditionally" is. - **Severity.** `critical` (data loss/security/crash on common paths), `high` (wrong behavior on a real path), `medium` (wrong behavior on an edge case), `low` (style, maintainability, non-functional). - **Verdict.** `CONFIRMED` (you reproduced it or traced it definitively) or `PLAUSIBLE` (strong reasoning, not independently verified). Never present a `PLAUSIBLE` finding as if it were `CONFIRMED`. ## Grounded checks come first Before opinion-based review, run what can actually be run: typecheck, the relevant tests, a manual exercise of the changed behavior. A defect a test or typecheck catches outranks a defect found by reading. Cite the tool output, don't restate an opinion a machine already settled. ## The merge gate There is no fixed numeric threshold. The gate is: **zero `CONFIRMED critical`/`high` findings** remain unaddressed. `PLAUSIBLE` findings and `low`/`medium` findings are judgment calls for the orchestrator/user. Surface them, don't silently drop them, but don't block on them unconditionally either. ## Fix loop discipline When a review finds defects and the engineer fixes them, the FIX gets reviewed again before confirming. The file version of the "final fix ships unreviewed" off-by-one bug is a known trap: always review the version of the code that's actually about to ship, not the version that was reviewed two edits ago. --- Source attribution: mgd34msu Original project: https://github.com/mgd34msu/goodvibes-plugin/blob/d19fa3c57eda377c032d3cd3e897fe127d1e99aa/plugins/goodvibes/skills/review-scoring/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2025 GoodVibes Contributors Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: mgd34msu Original project: https://github.com/mgd34msu/goodvibes-plugin/blob/d19fa3c57eda377c032d3cd3e897fe127d1e99aa/plugins/goodvibes/skills/review-scoring/SKILL.md Attribution basis: Source repository record Fields of work: Development & Engineering, Product Management Roles: QA / Test Engineer, Backend Developer, Frontend Developer, Product Manager, Technical Product Manager Specialties: Frontend, React, Word Documents, Git, API, Database, Testing Tools: Tool not specified Country applicability: Country not specified Classification basis: Source category, role and specialization labels Instruction SHA-256: a95728bd2234a85b3f7c3d91be8a8e8a496edd34d2ab145d7d3e89266e98941a