Agile V™ Agent Skills Library

Open Agent Skills for turning AI-assisted engineering into a reviewable chain from approved requirements to implementation, tests, independent verification, and human release decisions.

Agile V is a tool-agnostic, human-governed assurance layer for AI-assisted engineering. It gives agents explicit roles, durable evidence, typed traceability, independent challenge, risk-scaled controls, and stop points where accountable people approve requirements and release.

It does not replace your coding agent, engineering process, or judgment. It makes their inputs, outputs, checks, and decisions easier to inspect.

Without an assurance layer	With Agile V
Chat context becomes implicit build input	A reviewed requirement revision becomes the frozen baseline
Tests may mirror implementation assumptions	Test design is derived independently from requirements
The builder grades its own output	A separate verifier challenges specified behavior
Approval is implied by agent completion	Human Gates record authority, evidence, and residual risk
Traceability is reconstructed later	Typed links connect requirements, artifacts, tests, and evidence
Tool access follows runtime defaults	Risk-scaled controls bound data, tools, permissions, and side effects

Start in 60 Seconds

Install the minimal requirements profile into a project-level Agent Skills directory:

git clone https://github.com/Agile-V/agile_v_skills.git
mkdir -p .agents/skills
cp -R agile_v_skills/agile-v-core \
  agile_v_skills/requirement-architect \
  agile_v_skills/logic-gatekeeper \
  .agents/skills/

Ask your agent:

Load agile-v-core. Classify the risk of this change, identify missing context,
and create reviewable requirements before implementation: [describe change]

Correct behavior includes halting on material ambiguity, persisting requirements, and waiting for approval before treating a revision as the build baseline. For implementation, select a complete installation profile, then follow the Golden Journey.

Who It Is For

Use Agile V when:

• AI-assisted changes need reviewable requirements and explicit acceptance criteria.
• Implementation should be challenged independently rather than self-graded.
• Security, safety, regulatory, contractual, or operational risk requires durable evidence.
• Multiple agents or sessions need a stable baseline and reproducible handoffs.
• Humans must authorize requirements, waivers, residual risk, or release.

It is not:

• A certification, conformity assessment, legal opinion, or regulatory approval product.
• A substitute for domain experts, accountable engineering judgment, or organizational controls.
• A reason to add heavy process to every prototype or low-consequence experiment.
• An autonomous deployment system or a guarantee that an AI-generated result is correct.

Choose the smallest profile appropriate to the risk.

Repository Evidence

Proof point	Inspect it
49 skills	Machine-readable catalog/skills.json and the Skill Routing Guide
347 contract tests	Deterministic schema and repository tests under tests/
18 evidence schemas	Requirements, risk, builds, tests, verification, validation, approvals, traceability, controls, delegation, and AI provenance in schemas/
Five build domains	Python, JavaScript/TypeScript, NestJS, Dart/Flutter, and embedded C/C++
Public runtime contracts	Lifecycle, risk classification, and tool/delegation controls
Reproducible claims policy	Measurement inputs and methods are defined in PERFORMANCE.md

The repository is currently on the v3.9.x line. package.json is the repository-version source; each skill also carries its own contract version in YAML frontmatter.

Assurance Controls

Control	Practical effect
Halt and ask	Agents stop rather than inventing missing material requirements or constraints
Immutable baseline	Build and test roles consume the same approved revision
Independent contexts	Test design and verification avoid implementation-led confirmation bias
Human Gates	Accountable people approve requirements, exceptions, residual risk, and release
Risk scaling	Delivery levels L0-L4 select proportionate review and evidence
Decision logging	Significant choices retain rationale, alternatives, owner, and evidence links
Typed traceability	Records use appropriate lineage instead of forcing every item under one REQ link
Machine validation	JSON Schemas catch malformed structured evidence before release review
AI provenance	Material AI influence is recorded without secrets or hidden chain-of-thought

These are contracts and records, not proof by themselves. Teams must operate the controls, review the resulting evidence, and resolve failures.

Canonical Workflow

Intent
  -> risk classification
  -> persisted draft requirements
  -> independent ambiguity and constraint findings
  -> revision and Human Gate 1 approval
  -> frozen requirement baseline
  -> implementation + independent test design
  -> independent verification + Eval Gate
  -> intended-use validation when required
  -> evidence bundle + Human Gate 2
  -> release and monitoring

Stage	Role and boundary	Evidence
Requirements	requirement-architect persists and revises; logic-gatekeeper records findings but does not rewrite the draft	Approved REQ-XXXX revisions and baseline registration
Build	build-agent and one domain skill implement only from the frozen baseline	ART-XXXX -> implements -> REQ-XXXX lineage
Test design	test-designer derives tests from the baseline, not from implementation	TC-XXXX -> verifies -> REQ-XXXX lineage
Verification	red-team-verifier independently asks “Was the specified output built correctly?”	.agile-v/VERIFICATION_SUMMARY.md, test logs, VER-XXXX, and eval results
Intended-use validation	validation-agent, when required, separately asks “Was the right system built for representative users and conditions?”	VALIDATION_PLAN.md, VALIDATION_PROTOCOL.md, and VALIDATION_REPORT.md
Release	An authorized human reviews evidence and residual risk before release-manager proceeds	Gate 2 approval, release and rollback evidence

Verification does not prove intended-use acceptance. Intended-use validation does not close failed verification. Keep their roles and records separate. See the canonical lifecycle contract for states, lineage, and stop conditions.

When separate agents are unavailable, design tests before implementation and use a fresh context for verification to reduce contamination. Never let the Build Agent verify its own work.

Installation Profiles

Profile	Use when
core-minimal	Requirements, independent review, and lifecycle guidance
verified-build	Baselined implementation, independent test design, and verification
existing-repo	Gate 0 understanding, impact analysis, regression selection, and diff evidence
regulated	L3/L4, safety-relevant, sensitive, regulated, or externally assured work
business-preview	Locally evaluating draft business and executive-governance contracts

The Installation Profiles document lists exact skill directories and copy commands. Add one implementation domain when building. Agent Skills may be installed at project or user level, depending on the platform.

Platforms

Platform	Typical project directory	Guide
Claude Code	.claude/skills/	Repository guide · Official docs
Cursor	.cursor/skills/	Repository guide · Official docs
VS Code	.github/skills/ or .agents/skills/	Official docs
GitHub Copilot	.github/skills/ or .agents/skills/	Official docs
Other compatible agents	Platform-specific skills directory	AgentSkills.io integration guide

For detailed scenarios and retained platform examples, see EXAMPLES.md, CLAUDE.md, and CURSOR.md.

Skill Catalog

Load agile-v-core first, then only the roles needed for the stage and risk.

Category	Scope	Start here
Foundation and orchestration	Core directives, pipelines, lifecycle, quality gates, behavioral rules	agile-v-core
Discovery and requirements	Research, threats, UX constraints, formal requirements, independent findings	requirement-architect
Build and test	Language-agnostic build, five domains, hardware, independent test design	build-agent
Assurance	Independent verification, intended-use validation, safety, compliance	red-team-verifier
Delivery and operations	Product ownership, release, observability	release-manager
Existing repositories	System understanding, impact, regression, graph, and diff evidence	skills/
Business and C-Suite	Functional business execution and executive orchestration	Preview catalog

Use the complete routing guide for all 49 skills, prerequisites, status, and intent-to-skill mappings. The machine-readable source is catalog/skills.json.

Preview Boundary

A skill is preview/draft only when its current frontmatter contains metadata.status: draft. Presence on main does not make its contract stable.

Current preview contracts are:

• AI influence workflow: agile-v-aibom.
• GxP qualification (DQ/IQ/OQ/PQ evidence, intended-use validation, requalification): agile-v-gxp-qualification [Draft].
• Human oversight assurance: agile-v-human-oversight.
• Functional Business Track: venture-strategist, rd-innovator, gtm-executor, business-operations.
• C-Suite: c-suite-foundation, chief-exec, chief-tech, chief-finance, chief-people, chief-ops, c-suite-update.

Review, tailor, approve, and baseline preview outputs locally before operational use. C-Suite skills govern and coordinate; functional skills execute. Current status is maintained in the routing guide.

Standards and Compliance

Agile V provides engineering controls, evidence structures, and public-scope mappings. These materials may support an organization’s assurance work, but do not establish certification, regulatory approval, legal compliance, product safety, or organizational conformity. Applicability, tailoring, validation, qualified personnel, and accountable approval remain your responsibility.

Resource	Scope
Compliance posture	Coverage, boundaries, assumptions, and gaps
Compliance matrices	ISO 9001, ISO 13485, AS9100D, ISO 27001, and GxP/GAMP 5
Standards mappings	Lifecycle, AI governance, safety profiles, source register, and EU AI Act screening
Runtime schemas	Machine-readable evidence contracts and validation model
Control matrix	Data, tool, model, rights, gate, test, cost, and rollback controls
AI influence traceability	Model, runtime, context, tool, skill, artifact, and revalidation provenance

Sector terms such as ASIL, SIL, DAL, GxP, and regulatory risk categories are not interchangeable with Agile V delivery levels L0-L4. Use the risk classification contract and an applicable sector profile.

Learn and Compare

Resource	What it provides
Tutorials	Verified authentication, independent-agent verification, AI manifests, and regulated adoption
Golden Journey	Canonical end-to-end onboarding and evidence flow
Comparisons	Bounded comparisons with adjacent methods and tools
Examples	Concrete usage scenarios
Documentation hub	Runtime, standards, compliance, and integration documentation
Showcase	Evidence-based case-study requirements and submission format

Repository Structure

agile-v-core/                 foundation skill; load first
agile-v-*/                    lifecycle, governance, and quality skills
requirement-architect/        formal requirements and baselines
build-agent/                  language-agnostic implementation contract
domains/                      five language/platform build skills
test-designer/                independent baseline-derived test design
red-team-verifier/            independent verification
validation-agent/             separate intended-use validation
skills/                       existing-repository evidence agents
catalog/                      machine-readable skill catalog
schemas/                      18 JSON evidence schemas
templates/                    reusable project evidence records
tests/                        deterministic contract tests and fixtures
docs/                         tutorials, runtime, standards, and compliance

Each skill lives in one directory with one SKILL.md using the AgentSkills.io specification. Projects normally persist lifecycle evidence under .agile-v/; copy and tailor records from templates/agile-v/ rather than editing library templates in place.

Troubleshooting

If skills do not load or the agent starts coding without requirements:

1. Confirm the selected directory is supported by your platform and contains <skill-name>/SKILL.md.
2. Restart or reload the agent after installing skills.
3. Ask the agent to list or explicitly load agile-v-core.
4. Verify that you copied a complete installation profile, not isolated files.
5. Test with an ambiguous request; expected behavior is to classify risk and ask for missing context before synthesis.

See the platform guides for Claude Code and Cursor, the examples, or open an issue with the platform, install path, skill names, and observed behavior.

Community and Contributions

GitHub Discussions is the community forum. Use Issues for reproducible defects and focused proposals, and follow the Showcase guide for case studies.

Contributions are welcome. Read CONTRIBUTING.md, AGENTS.md, the Code of Conduct, and the Security Policy before submitting a pull request. New or changed skills must preserve traceability, halt-on-ambiguity behavior, independent verification, human gates, decision rationale, valid frontmatter, and applicable attribution.

License and Attribution

The Agile V™ Agent Skills Library is licensed under Creative Commons Attribution-ShareAlike 4.0 International. Contributions are accepted under the same license.

Selected context-engineering patterns are adapted from Get Shit Done (GSD) by Lex Christopherson under the MIT License. Skill-level adaptations and source details are recorded in YAML metadata.adapted_from fields and the standards source register.

Agile V™ is maintained by agile-v.org.