agentsclimarketplace

Spec driven development

Skill jacob-balslev/skill-graph/marketplace/skills/spec-driven-development

Use when starting a non-trivial feature, refactor, or agent implementation that needs a written spec, plan, task breakdown, and verification path before code changes. Covers Spec Kit-style SDD phases, requirements-vs-plan separation, task traceability, review gates, and spec-compliance verification. Do NOT use for one-line edits, README-only fixes, post-implementation code review (use `code-review`), or test-level decisions (use `testing-strategy`).From its SKILL.md

Install
npx -y skills add jacob-balslev/skill-graph --skill spec-driven-development

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

11.7 KB, ~1.9k tokens by cl100k_base, as published. Nobody here has run it

Spec Driven Development (SDD)

Concept of the skill

Use when starting a non-trivial feature, refactor, or agent implementation that needs a written spec, plan, task breakdown, and verification path before code changes.

Coverage

  • When to require SDD: non-trivial work, core-module refactors, ambiguous agent loops, cross-boundary changes, or any task where hidden requirements could be expensive after code exists.
  • Artifact chain: spec.md for what and why, plan.md for how, tasks.md for ordered work, implementation commits for execution, and a final verification report for spec compliance.
  • Phase discipline: specification before plan, plan before tasks, tasks before implementation, and verification before completion.
  • Traceability: each task and verification check maps back to a requirement, constraint, or success criterion.
  • Review gates: human approval when available, or an explicit documented rationale when autonomous work must proceed.
  • Scope control: if implementation discovers the spec or plan is wrong, update the upstream artifact before continuing.
  • Post-implementation learning: measure whether the change solved the problem when the task has a product, operational, or user-facing success metric.

Philosophy of the skill

AI agents default to implementation-first thinking: receive a prompt, start coding. That produces features that compile, pass narrow tests, and still miss the actual requirement. SDD makes the specification the source of truth and turns the plan, task list, implementation, and verification report into derived artifacts.

GitHub Spec Kit frames the core process as Spec → Plan → Tasks → Implement. This skill keeps that source shape and adds a final Verify gate because a skill application is not complete until the implementation is checked against the spec that justified it.

The most important separation is what versus how. The spec names user value, constraints, non-goals, and success criteria. The plan names architecture, contracts, data flow, testing, and risk. Collapsing those two artifacts creates design debt before the first file is edited.

Workflow

Use this workflow in order. If a phase reveals that an earlier artifact is wrong, update the earlier artifact first and restart from there.

1. Decide Whether SDD Is Required

Use the lightweight path only for small, local, reversible edits. Use SDD when any of these are true:

  • More than one module, service, schema, public API, or user flow may change.
  • Requirements are ambiguous or conflict with existing behavior.
  • Security, privacy, accessibility, data integrity, or migration risk is present.
  • An agent loop has stalled because it keeps discovering new scope while coding.

2. Specify (spec.md)

The specification defines the desired outcome without prescribing implementation mechanics.

  • Requirements: user-visible behavior, system behavior, and must-have outcomes.
  • Constraints: architecture boundaries, security/privacy rules, accessibility, performance, compatibility, and data handling.
  • Non-goals: what this change explicitly will not solve.
  • Success criteria: observable facts that prove the work is done.
  • Edge cases: zero states, failure states, concurrent access, volume limits, and rollback paths.

Anti-pattern: Describing implementation details (e.g., "Use a for loop") in the spec. The spec is for "What", not "How".

Exit gate: the spec is approved by the human owner, or the agent records why it is safe to proceed without explicit approval.

3. Plan (plan.md)

The plan translates the spec into an implementation strategy.

  • Architecture: affected modules, new components, storage/schema changes, migration path, and rollback strategy.
  • Data flow: how data moves between inputs, processing, storage, outputs, and external systems.
  • Contracts: API request/response shapes, events, schemas, status codes, and compatibility promises.
  • Testing: evidence needed at unit, integration, contract, E2E, manual, or visual levels.
  • Risks: hidden dependencies, breaking changes, sequencing hazards, and observability needs.

Exit gate: the plan explains how every success criterion will be implemented and verified.

4. Decompose (tasks.md)

Break the plan into ordered, testable tasks.

  • One behavioral change per task.
  • Each task names the spec requirement or plan section it satisfies.
  • Each task includes a verification command, check, or review step.
  • Dependencies are topologically ordered so prerequisite work appears first.
  • Parallel tasks are marked only when they can be executed without touching the same files or contracts.

Exit gate: a reader can execute tasks in order without rediscovering architecture decisions.

5. Implement

Implement from tasks.md, not from memory.

  • Complete tasks in dependency order.
  • Keep each commit or patch scoped to the task it claims.
  • If a task exposes a wrong requirement, update spec.md; if it exposes a wrong design, update plan.md; then regenerate or adjust tasks.
  • Do not silently add scope just because the implementation made it convenient.
  • Keep tests, docs, and operational checks attached to the task that requires them.

6. Verify

Verification is the only path to finality.

  • Spec compliance: every must-have and success criterion has evidence.
  • Plan compliance: implementation follows the chosen architecture or documents an approved change.
  • Regression evidence: focused tests, lint/type checks, contract checks, or manual verification ran.
  • User-facing quality: UI, copy, accessibility, and visual behavior match the spec and the project design system.
  • Documentation: repo instructions, API docs, decisions, and runbooks are updated when the behavior or workflow changed.
  • Residual risk: any skipped check has a named reason and owner.

7. Learn

When the spec has a product, operational, or user-facing metric, measure whether the change solved the intended problem.

  • Define the success metric before implementation.
  • Confirm the measurement mechanism exists.
  • Collect enough evidence for the decision.
  • Record whether to continue, adjust, or stop.

Skip the learning loop for pure infrastructure chores, small bug fixes with a regression test, and cosmetic edits with no measurable hypothesis.

Verification Checklist

SDD CHECK
=========
[ ] spec.md exists or the fast-track rationale is documented
[ ] spec.md separates requirements, constraints, non-goals, success criteria, and edge cases
[ ] plan.md maps each success criterion to architecture, contracts, data flow, and verification evidence
[ ] tasks.md is ordered, traceable, and verifiable
[ ] No code was written before the plan gate, or the exception is documented
[ ] Every implementation deviation updated the upstream spec or plan
[ ] Final verification confirms all spec success criteria
[ ] Eval, routing, or quality claims remain unverified unless the corresponding check actually ran

Do NOT Use When

Instead of this skillUseWhy
One-line edits, README-only fixes, or trivial local changesno dedicated skillThe SDD overhead is larger than the change risk
Reviewing code quality after implementationcode-reviewCode review owns diff-level correctness, risk, and merge-readiness assessment
Deciding what level of automated or manual testing is appropriatetesting-strategyTesting strategy owns test-level selection and regression targeting
Holistic completion scoring after work is doneevaluationEvaluation owns quality scoring and revision loops after implementation evidence exists

Verification

After applying this skill, verify:

  • Changes follow the patterns documented above
  • No regressions in affected functionality
  • The final report names which spec criteria were satisfied and which checks produced evidence

Skill Graph context

<!-- skill-graph-context:start (generated — do not edit by hand) -->

Classification

  • Subject: software-engineering-method
  • Public: true
  • Domain: engineering/methodology
  • Scope: Use when starting a non-trivial feature, refactor, or agent implementation that needs a written spec, plan, task breakdown, and verification path before code changes. Covers Spec Kit-style SDD phases, requirements-vs-plan separation, task traceability, review gates, and spec-compliance verification. Do NOT use for one-line edits, README-only fixes, post-implementation code review (use code-review), or test-level decisions (use testing-strategy).

When to use

  • Triggers: sdd-skill, planning-mode, spec-driven-development

Related skills

  • Verify with: testing-strategy, code-review
  • Related: evaluation, testing-strategy, code-review, prioritization, interaction-patterns

Grounding

  • Mode: hybrid
  • Truth sources: https://github.github.com/spec-kit/index.html, https://github.github.com/spec-kit/reference/workflows.html, https://github.com/github/spec-kit, https://standards.ieee.org/ieee/29148/6937/

Keywords

  • spec driven development, SDD, specification first, technical plan, task decomposition, spec.md, plan.md, tasks.md, requirements before code, phase gates
<!-- skill-graph-context:end -->

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most plan spec skills give in ~1.9k tokens

Counted across 1,099 of the 1,860 authors here whose files we hold, read 2026-08-07

  • Ask one question at a timein 51 of 1099
  • Break plans into vertical slicesin 29 of 1099, across 11 files
  • Publish issues in dependency orderin 27 of 1099, across 9 files
  • Iterate until user approves the breakdownin 25 of 1099, across 7 files
  • Explore the repository to understand the codebase statein 24 of 1099, across 7 files
  • Use domain glossary vocabularyin 23 of 1099, across 5 files
  • Apply correct triage labels to published issuesin 23 of 1099, across 5 files
  • Prefer AFK slices over HITLin 22 of 1099, across 7 files
  • Write a specification before writing any codein 22 of 1099, across 14 files
  • Write failing tests before implementation codein 22 of 1099, across 20 files
  • Ask clarifying questions until requirements are concretein 21 of 1099, across 13 files
  • Respect existing architecture decision recordsin 20 of 1099, across 5 files

Said here and by no other author read

  • Write spec defining what and why not how
  • Write plan translating spec into strategy
  • Write ordered tasks from plan
  • Implement tasks from the task list
  • Update upstream artifacts before continuing implementation
  • Record rationale if proceeding without human approval

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 326,790. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.