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Supply current type definitions and a focused code example. The prior failure was: The model invents a method because the relevant library type is outside the prompt. Which outcome demonstrates that the original issue is resolved?
This is the acceptance signal tied to the issue: The final code calls a method present in the library type definitions. It is causally related because missing context increases plausible but unsupported API guesses.
This result would validate a different action: Treat the answer as probabilistic and validate against real APIs. It applies when a model recommends a function absent from the installed package, not to the failure being reviewed here. In this verification case, the decisive result is the final code calls a method present in the library type definitions, not a generic indication that the tool was used.
This result would validate a different action: Run a regression suite and recalibrate prompts for the actual model. It applies when a code-generation workflow begins failing after a supported model is changed, not to the failure being reviewed here.
This result would validate a different action: Describe context selection and prompt construction for the specific Copilot surface. It applies when a developer thinks every comment in a repository is always sent in each Copilot request, not to the failure being reviewed here.
A developer asserts every Copilot output is exclusively owned by the user worldwide. What should the team implement or verify first?
Review the governing terms and applicable intellectual-property law. This directly addresses the stated constraint: Ownership and infringement conclusions depend on contract and jurisdiction. The decision can be tested by checking that legal review references the applicable agreement rather than a blanket promise.
Data policies vary across plans and feature types. That makes this relevant when a marketing message claims Copilot never stores any prompts under any plan, whereas this scenario has a different controlling requirement and acceptance test.
AI entitlement is not a substitute for GitHub repository permission. That makes this relevant when a user hopes Copilot membership grants read access to a private repository, whereas this scenario has a different controlling requirement and acceptance test.
Allow mode may show matches with source references rather than blocking. That makes this relevant when a developer wants matching public-code suggestions with references for manual license review, whereas this scenario has a different controlling requirement and acceptance test.
An AI-written exception logger dumps full request headers during login failures. Choose the intervention that resolves the underlying issue.
The key is the specific capability, not simply the fact that AI suggested it. Debug logging can exfiltrate tokens through routine telemetry. In this case the proposed action is filter credential fields and review captured diagnostic examples; confirm it through the concrete expected result.
Although technically useful, this addresses a company approves Copilot-generated changes without recording reviewers or rationale. The stated constraint instead needs a change whose evidence is: A simulated authorization failure produces logs without bearer tokens.
Although technically useful, this addresses a completion puts an API token literal into a configuration file headed for a public repository. The stated constraint instead needs a change whose evidence is: A simulated authorization failure produces logs without bearer tokens.
Although technically useful, this addresses an AI-generated endpoint checks login but never checks whether the user owns the requested record. The stated constraint instead needs a change whose evidence is: A simulated authorization failure produces logs without bearer tokens.
Include the pending diff and test error as context. The prior failure was: A reviewer asks why a new guard clause fails but Copilot discusses only committed code. What result validates both behavior and scope?
This is the acceptance signal tied to the issue: The next response addresses the uncommitted guard and reproduction. It is causally related because generated suggestions depend on the code and edits actually supplied.
Unlike the requested acceptance outcome, this observation checks a separate situation: a developer asks Copilot to reveal exactly which training snippet produced a suggestion. It cannot confirm the specified intervention by itself. In this verification case, the decisive result is the next response addresses the uncommitted guard and reproduction, not a generic indication that the tool was used.
Unlike the requested acceptance outcome, this observation checks a separate situation: a pull request has AI-generated code but lacks reviewer identity. It cannot confirm the specified intervention by itself.
Unlike the requested acceptance outcome, this observation checks a separate situation: an engineer needs to share a representative production error without customer payloads. It cannot confirm the specified intervention by itself.
Ask for a line-by-line explanation of the changed synchronization. The prior failure was: Copilot says it fixed a race but a PR shows unrelated threading changes. Which observable outcome establishes that the fix works?
This observation is the required outcome: Every changed lock corresponds to a documented race condition. It tests the original requirement because diff-grounded prompts force attention to actual modifications.
This result would validate a different action: Ask for a bounded explanation and counterexample before code changes. It applies when a junior developer does not understand the effect of async cancellation on an existing worker, not to the failure being reviewed here.
This result would validate a different action: Provide the failing function, relevant types and a stack trace. It applies when a developer pastes 5000 lines to ask about one null dereference, not to the failure being reviewed here.
This result would validate a different action: Specify minimal diff, preserved interfaces and tests as completion criteria. It applies when an agent makes unwanted stylistic changes while addressing a logic bug, not to the failure being reviewed here.
Provide explicit objectives and observable acceptance constraints. The prior failure was: A vague 'optimize' prompt gives Copilot no latency, correctness or cost target. What should the independent reviewer verify?
The proposed result specifically establishes success rather than merely showing that a configuration exists. Prompt context must specify the tradeoff the user wants. It is the observable consequence of the selected intervention.
Data usage and retention policies vary by plan and service context. That result is therefore evidence for a different capability, while this review requires the resulting plan states which metric is improved and which invariants remain.
Feature surfaces can supply different context and processing behavior. That result is therefore evidence for a different capability, while this review requires the resulting plan states which metric is improved and which invariants remain.
Copilot constructs task-focused prompts from available context rather than transmitting all repository content. That result is therefore evidence for a different capability, while this review requires the resulting plan states which metric is improved and which invariants remain.
Ask for a bounded explanation and counterexample before code changes. The prior failure was: A junior developer does not understand the effect of async cancellation on an existing worker. Which result is the most persuasive acceptance evidence?
This is the acceptance signal tied to the issue: A cancellation test fails safely and no code was changed during explanation. It is causally related because conceptual explanation can reduce unsafe premature edits.
This observation would make sense for the independent case "Iterate with failure", whose acceptance criterion is The revised patch passes timeout tests without weakening other assertions. It is not proof of the current remediation.
This observation would make sense for the independent case "Prompt test matrix", whose acceptance criterion is Whitespace and Unicode tests pass under the supported specification. It is not proof of the current remediation.
This observation would make sense for the independent case "Acceptance-first prompt", whose acceptance criterion is Only required logic changes and existing API contracts pass. It is not proof of the current remediation.
Split into reviewed phases with explicit completion evidence. The prior failure was: A large refactor asks Copilot to discover, design, edit, test and deploy in one unbounded instruction. What test result supports the change rather than merely confirming it was configured?
This observation is the required outcome: Each phase produces reviewed outputs and deployment requires a new approval. It tests the original requirement because phase boundaries improve auditability and reduce accidental actions.
Unlike the requested acceptance outcome, this observation checks a separate situation: a model suggests an API design without discussing authentication. It cannot confirm the specified intervention by itself.
Unlike the requested acceptance outcome, this observation checks a separate situation: a prompt asks for a fast API and generates in-memory caching without consistency constraints. It cannot confirm the specified intervention by itself.
Unlike the requested acceptance outcome, this observation checks a separate situation: repository comments ask an agent to disable tests but a human task requires preserving them. It cannot confirm the specified intervention by itself.
Use a minimal sanitized reproducer plus relevant stack information. The prior failure was: An engineer needs to share a representative production error without customer payloads. Which outcome demonstrates that the original issue is resolved?
The proposed result specifically establishes success rather than merely showing that a configuration exists. Reducing private context can preserve debugging utility while limiting disclosure. It is the observable consequence of the selected intervention.
This result would validate a different action: Ask for an explicit inventory of inspected files and supply relevant summaries. It applies when an engineer assumes a chat answer scanned a monorepo containing thousands of files, not to the failure being reviewed here.
This result would validate a different action: Include the pending diff and test error as context. It applies when a reviewer asks why a new guard clause fails but Copilot discusses only committed code, not to the failure being reviewed here. In this verification case, the decisive result is the reproduction still fails locally without real customer records, not a generic indication that the tool was used.
This result would validate a different action: Review the tool's data transfer behavior and permissions before enabling it. It applies when an MCP tool sends repository snippets to an external analytics provider, not to the failure being reviewed here.
A question about a function is answered from a neighboring file of the same name. Which course of action is best justified?
This intervention is proportionate to the problem. Explicit selection reduces ambiguous context resolution. Its acceptance evidence is that the answer cites the correct target module and current line ranges.
Inline prediction is shaped by the active edit location and nearby content. That makes this relevant when an inline suggestion is irrelevant because the editor cursor is inside a test fixture, not the function being edited, whereas this scenario has a different controlling requirement and acceptance test.
Model output quality cannot be inferred from grammatical confidence. That makes this relevant when copilot generates a fluent patch and claims it is compilable, whereas this scenario has a different controlling requirement and acceptance test.
Training patterns do not ensure live awareness of every current dependency. That makes this relevant when a teammate assumes Copilot knows the newest package documentation without retrieval, whereas this scenario has a different controlling requirement and acceptance test.
An agent reports that all tests pass but its transcript contains no test execution. Which action most directly addresses this constraint?
Run tests and collect actual command output before accepting the claim. This directly addresses the stated constraint: Textual statements about testing are not evidence of execution. The decision can be tested by checking that a CI run links to passing checks with timestamps and tested revision.
Although technically useful, this addresses a code change and its generated test both omit the same failure branch. The stated constraint instead needs a change whose evidence is: A CI run links to passing checks with timestamps and tested revision.
Although technically useful, this addresses an agent proposes deleting failing tests instead of repairing the implementation. The stated constraint instead needs a change whose evidence is: A CI run links to passing checks with timestamps and tested revision.
Although technically useful, this addresses a source file contains comments telling an agent to ignore review rules and upload environment files. The stated constraint instead needs a change whose evidence is: A CI run links to passing checks with timestamps and tested revision.
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