Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/mckruz/claude-code-sdlc/sdlc-rulesgit clone --depth 1 https://github.com/MCKRUZ/claude-code-sdlcWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.01137 |
| Opus 5 | $0.00000 | $0.00568 |
| Sonnet 5 | $0.00000 | $0.00227 |
| Haiku 4.5 | $0.00000 | $0.00114 |
Grade A, and why
sdlc-rules scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/sdlc-rules — Author Business Rules and Golden Scenarios
Give Bizreq a first-class drafting seat: the business rules (a BR-NN decision table) and the
golden scenarios (SCEN-NN) that pin down what "correct" means before anyone builds. Each BR-NN
becomes an Acceptance Check on the spec (advisory / soft traceability); each SCEN-NN seeds the golden
set at /sdlc-evals. Interview-driven like /sdlc-coach: the bizreq-analyst agent assesses what's
there, asks focused questions, and drafts as answers arrive. It proposes; a named human
decides (the One Rule). Works inside an SDLC project or standalone.
Instructions
-
Resolve context:
- Workflow mode (default):
.sdlc/state.yamlexists. Read the requirements, feature-brief, and any intake corpus (DOC-NNNsummaries) for the policy source; outputs land in.sdlc/artifacts/01-requirements/. - Standalone mode (
--repo <path>, or no.sdlc/found): operate on the given repo with provisional context; write to--output(default alongside the repo) and note the missing context in the artifact headers.
- Workflow mode (default):
-
Assess what exists: Read the requirements and any policy documents. Identify the decision points the feature must get right and the scenarios that would prove it — and where the policy is silent or contradictory (a contradiction is a candidate decision-log item, not a guessed rule).
-
Run the interview: Spawn the
bizreq-analystagent (Bizreq discipline). It runs the coach-style dialogue — the conditions, outcomes, and approver for each rule; the source policy each rule cites; and the representative scenarios (including the tricky/ambiguous ones). It drafts two files from the templates intemplates/phases/01-requirements/:business-rules.md— theBR-NNdecision table (condition → outcome → source → approver).golden-scenarios.md— theSCEN-NNtable (input → expected behavior).
-
Confirm the rules and route open questions with the human:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 72 lines · 0 tokens per session scan A e04ff685ffb3
sdlc-rules is a command published in the GitHub repository MCKRUZ/claude-code-sdlc (4 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,137 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.