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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11SpeckKeep is a command-line tool that organizes AI-assisted feature work around reviewable files: specifications, plans, tasks and verification evidence. Its default workflow moves from a project constitution to a spec, plan and task list, then implementation and archival. It is designed to keep people and coding agents aligned without leaving requirements only in chat.
What SpeckKeep does
SpeckKeep describes itself as “strict, lightweight spec-driven development for coding agents.” Rather than treating a feature request as a prompt that disappears into an agent session, it stores the work’s requirements and progress in plain files in the project. The intended result is a record people can review and agents can use as they move through implementation.
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The project identifies SpeckKeep as the successor to archived DraftSpec and documents a speckeep migrate command for migration from that predecessor. It also supports importing feature packages from OpenSpec and GitHub Spec Kit. See the SpeckKeep repository and documentation for the current instructions.
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How the workflow is organized
The project’s default path is constitution → spec → [inspect] → plan → tasks → implement → archive. Inspection is optional and happens before planning; verify is an optional, on-demand audit rather than a mandatory phase in that sequence. Commands such as challenge, handoff, hotfix, scope and recap are available at different points in the workflow.
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1. Set the project constitution
The constitution establishes the project-level expectations that should shape feature work. It gives the agent context beyond the immediate feature request.
2. Define the spec
A feature’s spec.md records requirements and acceptance criteria. SpeckKeep uses stable IDs for requirements and acceptance criteria, making it possible to refer to individual expectations as planning and implementation proceed.
3. Inspect, if useful
The optional inspect.md stage acts as a quality gate before planning. It is a place to examine the feature or codebase before committing to a design and task breakdown; it can be skipped when it does not add value.
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4. Plan and break work into tasks
plan.md captures design decisions and incremental delivery. tasks.md turns the plan into executable tasks, with surface maps and phase grouping. Depending on the feature, the project directory may also contain data-model.md for entities, fields and invariants, plus API or event contracts.
5. Implement and record proof
Tasks are checked off as they are completed, but a checked task is not considered done without a Proof: entry directly beneath it in tasks.md. The project’s example uses code and test evidence. This ties completion to a recorded basis rather than a status mark alone.
6. Verify or archive
verify.md can hold verification evidence. The README says archival is allowed when every checked task has proof, or after verify: pass. The speckeep check and speckeep archive commands block checked tasks that lack proof, while trace presents the evidence. Use verify when an on-demand audit is appropriate; it is distinct from the proof required for checked tasks.
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Using SpeckKeep with a coding agent
SpeckKeep’s support model is skills-first. Initialization installs a shared spec-driven-development overview and directly invocable phase skills in the agent’s standard skills directory. The files provide a common workflow for different agents, while feature artifacts remain in the project directory.
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The project lists 19 agent adapters in its README, including Claude Code, Codex, GitHub Copilot, Cursor, OpenCode, aider, Amazon Q, Gemini, Jules, Cline, Devin, Goose, Refact, Windsurf and Qwen Code. This is a project-maintained count, checked in the README on October 7, 2026, not an independently audited compatibility figure; adapter availability may change. The README says Continue.dev support was dropped after reports that the product was discontinued; that explanation is the project’s own.
To start, choose an installation route, initialize SpeckKeep for the intended agent, then work through the generated phase skills and feature files. The repository’s CSV-export example illustrates the flow: define acceptance criteria, inspect and plan, split implementation and tests into tasks, record verification evidence, and archive. It is an example of intended use, not independent evidence of results.
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Installation options
The project documents several ways to install the CLI. Its quick start also demonstrates using npx speckeep without a persistent installation. Installation details and commands can change, so use the current instructions in the project README rather than relying on a copied command from an older guide.
- Shell installer for Linux and macOS, with an option to pin a version.
- PowerShell installer for Windows.
- Homebrew or Scoop package managers.
- npm or Go installation.
npx speckeepfor an invocation without persistent installation.
The README also documents self-check and self-upgrade commands. Because the reviewed documentation does not establish a current release version or detailed platform compatibility matrix, check the project’s live installation guidance for the version and environment you use.
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Checks in a team or CI workflow
For teams that want enforcement beyond an individual’s local workflow, SpeckKeep documents a GitHub Action. It installs SpeckKeep, detects changed active feature folders and runs speckeep guard on each. According to the project, the action fails a pull request when a touched feature is not closeable. This makes the file-based completion rules available as a CI gate, though the project documentation alone does not establish that adopting the gate improves software outcomes.
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How SpeckKeep positions itself against OpenSpec and Spec Kit
The following is the SpeckKeep authors’ characterization of the options, not an independent benchmark or controlled comparison:
| Project | Workflow style | Context and artifact overhead | Brownfield fit and collaboration | Positioning |
|---|---|---|---|---|
| SpeckKeep | Strict phase chain | Described as low artifact overhead | Presented as suitable for real, existing codebases; emphasizes traceable work files | Lean, strict spec-driven development |
| OpenSpec | Fluid and artifact-guided | Not quantified in the reviewed project comparison | Not quantified in the reviewed project comparison | Artifact-guided workflow |
| GitHub Spec Kit | Thorough | Described as higher-overhead | Not quantified in the reviewed project comparison | More thorough process |
The comparison provides a useful snapshot of how SpeckKeep distinguishes its process, but it does not establish relative speed, correctness, handoff cost or suitability for a particular team. Choose based on how much structure your work needs, how much context you want to maintain, and whether your team will actually keep the artifacts current.
When it may fit an existing codebase
SpeckKeep’s artifacts do not require a project to begin as a greenfield build: its project description explicitly positions the workflow for real codebases, and its optional inspection stage can precede planning. It may suit a team that wants acceptance criteria, decisions, tasks and evidence kept together and reviewable during agent-assisted changes.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsThe trade-off is process discipline. Stable IDs, task breakdowns and proof entries create a stronger trail than an informal prompt, but they also require people and agents to maintain files as work changes. For a tiny edit, this structure may cost more than it saves; for a feature with several acceptance criteria, contributors or verification steps, the traceability may be useful. Those are workflow considerations, not measured claims about SpeckKeep’s performance.
What SpeckKeep does—and does not—establish
The project documentation explains the workflow, adapters, installation routes and enforcement commands. It does not provide an independent performance study showing that SpeckKeep improves first-try correctness or reduces handoff costs. Its qualitative benefits should therefore be read as the project’s rationale, not as demonstrated outcomes.
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