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feat: add PR Impact Analyzer prompt #5375
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feat: add PR Impact Analyzer prompt #5375
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documentation/src/pages/prompt-library/data/prompts/pr-impact-analyzer.json
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Intermediate prompt that analyzes pull requests by combining GitHub data fetching with Developer code analysis to generate structured impact reports with risk assessment and actionable review priorities. Signed-off-by: Shivam Gawali <[email protected]>
Changed from archived @modelcontextprotocol/server-github to the official @github/github-mcp-server as recommended by maintainer. Signed-off-by: Shivam Gawali <[email protected]>
Changed from npx to Docker-based installation using ghcr.io/github/github-mcp-server as documented in the official GitHub MCP server repository. This follows the maintainer's recommendation to use the official MCP server instead of the archived one. Signed-off-by: Shivam Gawali <[email protected]>
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Hi @shiv669 ! Thank you so much for your contribution. Once the tests run, I'll be able to merge your PR. ❤️ |
* main: Auto-compact Threshold UI improvements (#5354) Filter preserved user messages to be text only. (#5391) include sessionId in tool request (#5394) feat: add PR Impact Analyzer prompt (#5375) docs: add blog post on configuring goose for team environments (#5380) migrating back with new chatrecall non underscore name (#5223) fixing typo in blog metadata (#5382) feat: add new blog entry on adopting Goose in the enterprise (#5381) Blog/acp intro oct 2024 (#5379) feat: add A/B test framework generator recipe (#5378) Doc: (blog) - Deep Dive into goose's Extension System and Model Context Protocol (MCP) (#5291) Some system prompt tidying (#5313) Fix scheduler jobs dates formatting (#5368) Use Instructions as Prompt in Scheduler (#5359) feat(snowflake): add support for newer Claude 4.5 and 4 models (#5350)
* main: Feat/add mermaid chart rendering (#5377) Set up Datadog metrics for prompt injection detection (#5385) fix: restore --resume functionality for most recent session (#5401) Gemini again (#5390) docs(prompt-library): add github-issue-labeler intermediate prompt (#5374) docs: add Linux and Windows paths to uninstall section (#5371) fix: --session-id shouldn't work without --resume, but --name should (#5360) Auto-compact Threshold UI improvements (#5354) Filter preserved user messages to be text only. (#5391) include sessionId in tool request (#5394) feat: add PR Impact Analyzer prompt (#5375) docs: add blog post on configuring goose for team environments (#5380) migrating back with new chatrecall non underscore name (#5223)
* 'main' of github.com:block/goose: (132 commits) Fix/icon ii (#5413) Enable runtime access to provider name (#5399) fix: ensure trailing newline in files created by `text_editor` tool (#5336) docs: September 2025 Community All-Stars (#5411) make supports_cache_control async to avoid block in place (#5362) Send all the logs we output (#5363) Recipe variables (#5365) Feat/add mermaid chart rendering (#5377) Set up Datadog metrics for prompt injection detection (#5385) fix: restore --resume functionality for most recent session (#5401) Gemini again (#5390) docs(prompt-library): add github-issue-labeler intermediate prompt (#5374) docs: add Linux and Windows paths to uninstall section (#5371) fix: --session-id shouldn't work without --resume, but --name should (#5360) Auto-compact Threshold UI improvements (#5354) Filter preserved user messages to be text only. (#5391) include sessionId in tool request (#5394) feat: add PR Impact Analyzer prompt (#5375) docs: add blog post on configuring goose for team environments (#5380) migrating back with new chatrecall non underscore name (#5223) ...
Signed-off-by: Shivam Gawali <[email protected]> Signed-off-by: Blair Allan <[email protected]>
What This Prompt Does
This prompt helps you quickly understand the impact of a pull request before diving into code review. Instead of manually piecing together what changed and why it matters, you get an automated analysis that tells you exactly where to focus your attention.
The prompt uses two extensions working together. First, the GitHub extension pulls all the PR data like file diffs, commits, and metadata. Then the Developer extension takes that raw data and actually analyzes the code changes to figure out what systems are affected, what could break, and what needs careful review.
Why This Integration Works
When you're reviewing a large PR, you need two things. You need the context about what changed, which GitHub provides. But you also need to understand the technical implications of those changes, which requires analyzing the actual code. Thats where Developer comes in.
For example, if someone adds a new Redis dependency in their PR, the GitHub extension sees that package.json changed. But the Developer extension is what notices theres no connection pooling configured and flags it as a risk. The GitHub part fetches the facts, the Developer part understands what those facts mean for your system.
What Makes It Useful
The output is structured specifically for how developers actually review code. You get a quick risk assessment at the top so you know if this needs 15 minutes or an hour. Then it breaks down which systems are affected with actual risk levels, not just generic warnings.
The checklist section gives you specific things to verify before approving, like whether tests exist for the new rate limiter or if the database migration has a rollback plan. These arent vague suggestions like "check the tests" but concrete items tied to the actual changes in the PR.
It also assigns estimated review times and suggests specific reviewers based on what changed. If the PR touches authentication, it knows to loop in your security lead. If theres a database migration, it tags your DevOps team.
How Its Different
Most PR analysis tools just list changed files and line counts. This prompt actually reads the code and understands the architecture. It catches things like hardcoded configuration that should be in environment variables, or missing error handling in critical paths, or new dependencies that need infrastructure setup.
The risk detection isnt based on simple rules. It actually looks at the code patterns. If you add Redis without pooling config, it flags that. If you change auth middleware without adding tests, it catches it. If you introduce a breaking API change without updating docs, it points it out.
Real World Example
Say your teammate opens a PR adding rate limiting. Without this prompt, youd open the PR, see 12 files changed, start reading through the diff trying to figure out what this affects, whether its safe, what could go wrong.
With this prompt, you immediately see that it touches your auth system which is high risk, adds a database migration which needs coordination, and is missing tests for the new rate limiter. You know to spend time on the Redis configuration and make sure theres a rollback plan for the migration. The whole review becomes focused instead of exploratory.
Technical Details
Extensions Used:
Output Structure:
Format:
Closes
Intermediate Prompt Submission issue (closes #4770 once claimed)
Email for Credits
[email protected]