Problem Statement
Background
In the current Spec-Kit workflow, the typical structure generated during specify and plan includes multiple specification files such as:
- Feature specification
- Architecture / technical plan
- Implementation tasks
This works well for human-driven development, where developers manually implement the code, run tests, and decide whether the implementation satisfies the requirements.
However, in AI-driven development workflows, especially those using autonomous coding agents, there is an important missing component: a structured verification specification that defines how the implementation should be validated.
Problem
Without a machine-readable or structured verification specification, AI agents face several challenges:
-
No clear completion criteria
The agent cannot reliably determine when the task is finished.
-
No standardized validation process
Validation steps (tests, linting, build, etc.) are implicit rather than explicitly defined.
-
Weak support for iterative agent loops
Modern AI coding workflows rely on iterative execution loops (e.g., implement → verify → fix → verify) until success. Without a verification spec, this loop becomes unreliable.
This becomes particularly important for agent-based workflows such as autonomous coding systems, where the agent needs deterministic rules for validating progress.
Proposal
Introduce an additional spec file, for example:
or
This file would explicitly define how the implementation should be verified.
Example structure:
/specs
feature-spec.md
plan.md
tasks.md
verification-spec.md
Example Verification Spec
Example content for verification-spec.md:
# Verification Specification
## Build
The project must build successfully:
make build
## Unit Tests
All tests must pass:
go test ./...
## Lint
The code must pass lint checks:
golangci-lint run
## Integration Tests
Start the service:
docker compose up
Run API tests:
scripts/test_api.sh
Expected result:
- HTTP 200 responses
- JSON schema matches specification
## Performance (optional)
Benchmark must reach:
TPS >= 5000
Run:
scripts/benchmark.sh
Benefits
Adding a verification spec would significantly improve Spec-Kit's compatibility with AI-assisted and autonomous development workflows, including:
- AI coding agents
- iterative execution loops
- automated implementation pipelines
It enables a clear workflow like:
spec → plan → tasks → implement → verify → fix → verify
This kind of loop is increasingly common in modern AI coding environments and helps agents reliably determine success conditions.
Optional Future Direction
A more advanced version could support a machine-executable verification format, such as:
verify:
- cmd: make build
- cmd: go test ./...
- cmd: golangci-lint run
This would allow agents to directly execute the verification steps without manual interpretation.
Summary
Adding a verification-spec would:
- provide explicit acceptance criteria
- improve automation compatibility
- support modern AI-driven development loops
This could make Spec-Kit significantly more powerful for agent-based development workflows.
Would love to hear thoughts from maintainers and the community.
Proposed Solution
verification-spec.md
Alternatives Considered
No response
Component
Specify CLI (initialization, commands)
AI Agent (if applicable)
None
Use Cases
No response
Acceptance Criteria
No response
Additional Context
No response
Problem Statement
Background
In the current Spec-Kit workflow, the typical structure generated during
specifyandplanincludes multiple specification files such as:This works well for human-driven development, where developers manually implement the code, run tests, and decide whether the implementation satisfies the requirements.
However, in AI-driven development workflows, especially those using autonomous coding agents, there is an important missing component: a structured verification specification that defines how the implementation should be validated.
Problem
Without a machine-readable or structured verification specification, AI agents face several challenges:
No clear completion criteria
The agent cannot reliably determine when the task is finished.
No standardized validation process
Validation steps (tests, linting, build, etc.) are implicit rather than explicitly defined.
Weak support for iterative agent loops
Modern AI coding workflows rely on iterative execution loops (e.g., implement → verify → fix → verify) until success. Without a verification spec, this loop becomes unreliable.
This becomes particularly important for agent-based workflows such as autonomous coding systems, where the agent needs deterministic rules for validating progress.
Proposal
Introduce an additional spec file, for example:
or
This file would explicitly define how the implementation should be verified.
Example structure:
Example Verification Spec
Example content for
verification-spec.md:Benefits
Adding a verification spec would significantly improve Spec-Kit's compatibility with AI-assisted and autonomous development workflows, including:
It enables a clear workflow like:
This kind of loop is increasingly common in modern AI coding environments and helps agents reliably determine success conditions.
Optional Future Direction
A more advanced version could support a machine-executable verification format, such as:
This would allow agents to directly execute the verification steps without manual interpretation.
Summary
Adding a
verification-specwould:This could make Spec-Kit significantly more powerful for agent-based development workflows.
Would love to hear thoughts from maintainers and the community.
Proposed Solution
verification-spec.md
Alternatives Considered
No response
Component
Specify CLI (initialization, commands)
AI Agent (if applicable)
None
Use Cases
No response
Acceptance Criteria
No response
Additional Context
No response