Test -creating a impact analysis agent

[dulanwithanage]

Elaborated Requirement

Issue: #3 — Impact Analysis Agent for PR Merges
Type: Story
Verdict: NEEDS CLARIFICATION

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Summary

A developer or tech lead wants an AI-powered agent that automatically analyses the downstream impact of merging a pull request into the project. The underlying intent is to reduce the cognitive load on reviewers who must manually trace how a change propagates across the codebase — catching breaking changes, affected modules, and risky dependencies before they reach production. Success is defined as the agent surfacing a concise, accurate impact report at PR merge time that reduces post-merge incidents caused by overlooked side effects. This fits naturally alongside the existing PR Review Agent (which focuses on code quality) and the Requirement Analysis Agent (which focuses on intent alignment), forming a third pillar of automated engineering guardrails in this platform.

Dimension	Detail
Stated need	An agent that identifies the impact when merging a PR to the project
Underlying intent	Prevent unintended side effects from reaching production by surfacing affected areas automatically, without the reviewer needing to manually trace dependencies
Success definition	Reviewer receives a clear impact report (affected modules, risk level, potential breakage) before or at the point of merge, enabling a confident go/no-go decision
Current workaround	Reviewers manually inspect changed files, cross-reference callers, and rely on test suite coverage — a slow, error-prone, and experience-dependent process

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User Context & Workflow

• Who & when: Primarily a developer or tech lead reviewing a PR under time pressure; also useful for an author self-reviewing before requesting review. Context is typically high-stress: release windows, sprint deadlines, or incident hotfixes where the cost of a missed side effect is high.
• Constraints: Must integrate non-intrusively into the existing PR workflow (GitHub webhook or PR comment trigger); output must be scannable in under 60 seconds; must not block the merge process — advisory only unless configured otherwise.
• Workflow:
  1. A PR is opened or updated against the main/target branch
  2. The impact analysis agent is triggered (via webhook, GitHub Action, or PR comment command)
  3. Agent analyses the diff — changed files, functions, interfaces, data contracts
  4. Agent traces call graphs, module dependencies, and shared data structures to identify affected areas
  5. Agent posts a structured impact report as a PR comment (e.g., affected modules, risk rating, suggested areas to test)
  6. Reviewer reads the report alongside the PR Review Agent output and makes a merge decision
• Decision points: Whether to block merge on high-risk impact (human decision vs automated gate); which branches/environments are in scope; whether to include test coverage gap analysis as part of the impact report.

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Domain Context

• Key concepts:
  • Impact in this context means: which other modules, services, APIs, consumers, or data flows are likely to be affected by the changed code — not just what files changed, but what depends on those files.
  • PR merge impact differs from static analysis: it is relational (dependency graph traversal) rather than just syntactic.
• Business rules:
  • Impact should be assessed relative to the target branch (not just the PR branch in isolation).
  • Indirect dependencies (e.g., A calls B, B calls C — a change to C affects A) should be surfaced, ideally up to a configurable depth.
  • The report should distinguish between confirmed impact (direct callers changed) and potential impact (indirect or inferred).
• User expectations: Fast enough to complete before a reviewer finishes reading the diff (target: under 2 minutes); trustworthy enough that a false negative (missed impact) is rare; simple enough that the report requires no interpretation.
• Competitive/industry patterns:
  • GitHub's own Copilot PR summaries provide diff summaries but do not perform dependency-level impact tracing.
  • Tools like Codecov, SonarQube, and Nx affected graph analysis are adjacent but narrower (test coverage gaps or monorepo task graphs respectively).
  • Commercial tools like Moderne, Sourcegraph, and CodeScene offer call-graph analysis; the differentiator here is tight integration with the existing xianix agent platform and its GitHub webhook pipeline.
  • The PR Review Agent in this repo already indexes the codebase before review — this agent can reuse that index as a dependency graph input, avoiding duplicate work.

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Gaps & Unresolved Questions

#	Gap / Question	Severity	Suggested question
1	Scope of "impact" is undefined — does it mean module/file dependencies, API contract changes, database schema effects, or all of the above?	CRITICAL	What types of impact are in scope for the first version — call graph / file dependencies only, or also API contracts and data schema changes? — @dulanwithanage
2	Trigger mechanism is not specified — is this agent triggered via GitHub webhook (like the PR Review Agent), a PR comment command, or a GitHub Action step?	CRITICAL	Should the impact analysis agent be triggered automatically on PR open/update (webhook), or on demand via a PR comment (e.g., /analyse-impact)? — @dulanwithanage
3	Language and framework scope is unclear — the codebase appears to be .NET/C# based; does the agent need to support multiple languages or only the languages in this repo?	WARNING	Is the agent expected to analyse only the languages in this repository, or should it be language-agnostic for reuse across other projects? — @dulanwithanage
4	Output format and destination are not defined — where does the report appear (PR comment, separate dashboard, Slack) and what structure is expected?	WARNING	Should the impact report be posted as a structured PR comment (similar to the PR Review Agent), or delivered through a different channel? — @dulanwithanage
5	Relationship to the existing PR Review Agent codebase index is unexplored — reusing the index could save significant effort	INFO	Can the impact analysis agent reuse the codebase index already built by the PR Review Agent, or does it need its own indexing strategy? — @dulanwithanage
6	"Test -" prefix in the title suggests this may be an exploratory/spike issue rather than a committed story	INFO	Is this a spike to evaluate feasibility, or a committed story to deliver the agent? Clarifying this will affect sizing and definition of done. — @dulanwithanage

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Risks, Dependencies & Assumptions

• Value & priority: This is a high-value addition to the agent platform — it addresses a real pain point (missed side effects at merge time) that neither the PR Review Agent nor the Requirement Analysis Agent covers. Time sensitivity is moderate; no blocking dependency on other in-flight work identified. MVP scope should be limited to file/module dependency tracing only.
• Risks:
  • False negatives (missed impact) are more damaging than false positives — the agent must err on the side of over-reporting.
  • Codebase indexing cost for large repos may make the agent slow; mitigation is incremental/cached indexing tied to the target branch state.
  • Dynamic dispatch and reflection in .NET/C# can make static call graph analysis incomplete; the report should communicate confidence levels.
• Dependencies:
  • PR Review Agent codebase indexing infrastructure (potential reuse — see Gap Impact Analyst agent implementation #5).
  • GitHub webhook pipeline already in place in this repo (confirmed via PR Enhance PR Review Agent with codebase indexing and error handling imp… #2 and commit history).
  • Claude/LLM API for natural language impact summarisation (already in use across the platform).
• Assumptions:
  • The target repository for analysis is the same repo the agent is configured against (not a cross-repo dependency graph).
  • The agent will post output as a PR comment, consistent with the PR Review Agent pattern.
  • This is not intended to act as a merge gate (blocking) in its first version — advisory only.

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Groomed by req-analyst on 2026-03-26. Resolve CRITICAL gaps before sprint planning.