Requirements and SDLC documentation
SRS Skills: Standards-Driven Software Documentation
A public SDLC documentation engine for vision, requirements, architecture, design, testing, deployment, operations, governance, and AI-enabled systems.
Inspect on GitHub SRS SkillsRepository facts verified locally on 22 August 2026
Direct answer
SRS Skills helps product owners, business analysts, architects, delivery teams, testers, operators, and reviewers build a shared documentation trail from agreed scope to release and operational handover. It supports Waterfall, Agile, and Hybrid delivery when the workflow and evidence are defined.
Who it serves
Teams delivering software that need traceable requirements, design decisions, acceptance evidence, testing, release documentation, and governance.
157
Active catalogue entries reported
158
Local SKILL.md files including router
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Delivery models
main
Repository branch
Non-negotiable operating rule
Human in the middle. Every time.
Nothing is considered finished merely because an AI tool or skills engine produced it. A responsible person reviews the facts, logic, sources, calculations, code, security, privacy, context, and quality of the output before it is published, deployed, submitted, or used to make a decision. For some actions, the engine must stop until the user explicitly types that they approve the action; approval must never be inferred from silence or a vague request.
Human responsibility: approve, correct, escalate, reject, stop, or roll back the work.
Engine responsibility: make the method, evidence, limits, review points, and approval pauses visible.
In practice
A second view of the work this engine supports
The visuals illustrate the domain; they do not replace evidence, controls, or the human review required before a consequential decision or action.
Capability map
What this engine covers
The list below is a plain-language summary of the repository's verified capability surface. It is not a promise that every project needs every skill.
- Strategic vision, requirements, business analysis, process modelling, business rules, traceability, and acceptance criteria.
- Architecture and design documentation, coding guidelines, development artefacts, test plans, and test reports.
- Deployment, operations, monitoring, infrastructure, governance, compliance, and handoff documentation.
- AI-on-SaaS, agent, responsible-AI, incident-response, compliance, and accounting-engine documentation routes.
How to use it
A repeatable route from request to evidence
Establish intent
Capture the vision, decision, stakeholders, scope boundaries, constraints, risks, and evidence needed for approval.
Make it traceable
Connect requirements, business rules, process flows, architecture, design, tests, and operational obligations.
Test the contract
Define acceptance, normal paths, failure paths, security, performance, accessibility, and governance evidence.
Release and hand over
Package the delivery record, deployment guidance, operating responsibilities, monitoring, and recovery route.
Good fit
When to use this engine
- A software project needs an SRS, requirements baseline, architecture document, test plan, or deployment guide.
- An AI feature or agent needs an explicit model, data, evaluation, red-team, cost, human-oversight, and rollback record.
- Multiple teams are losing decisions between phases and need a traceable handoff.
- A regulated or high-consequence system needs evidence rather than an informal project brief.
Boundaries
What it does not replace
- It produces documentation methods and evidence structures, not project facts, implementation, or professional sign-off.
- The content and structure of a specification remain distinct from visual formatting and presentation design.
- It does not create evidence merely by writing confidently; source claims and project facts still need verification.
- It does not remove accountable human review, specialist judgement, approval authority, or professional sign-off.
- It does not authorise live account changes, client communications, production changes, or submissions without explicit permission.
Continue the route
Related first-party guidance
Chwezi Dev Engine
Route implementation, architecture, AI engineering, code, APIs, and infrastructure to the engineering engine.
Design System Skills
Route visual and typographic decisions for documents, interfaces, and design systems to the design engine.
SRS Skills on GitHub
Inspect the public phase-placed skills and documentation contracts.
Frequently asked
Questions about SRS Skills
What does SRS Skills cover?
It covers software documentation from strategic vision and requirements through architecture, design, testing, deployment, operations, and governance.
Does SRS Skills support Agile?
Yes. The repository supports Waterfall, Agile, and Hybrid delivery where the relevant workflow and evidence are defined.
Can it document AI agents?
Yes. The repository includes AI-on-SaaS, agent, responsible-AI, evaluation, red-team, cost, rollout, incident, compliance, and governance documentation routes.
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