GitHub collection
tikalk/adlc-team-skills
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21 skills imported from this repository.
architect-implement
Generate a full Architecture Description (AD.md) from accepted ADRs using multi-agent DAG orchestration. Use when accepted ADRs exist and you need to produce or update unified architecture documentation.
change-clarify
Review, accept, reject, or defer Change Decision Records (ChDRs) discovered by change-init. Interactive one-ChDR-at-a-time workflow that validates inferred decisions against their git/issue evidence before promotion to project memory.
change-init
Mine git history for Change Decision Records (ChDRs) by detecting commit messages that link to issue trackers, clustering the commits into change stories, and inferring the decisions behind them. Use when bootstrapping project memory from an existing repo's history (brownfield),
change-publish
Promote accepted Change Decision Records (ChDRs) from drafts to project memory at .adlc/memory/chdr/, write OKF-style frontmatter, and regenerate the boot-facing .adlc/memory/chdr.md index that team-boot injects at session start. Use after /change-clarify has accepted ChDRs.
evals-analyze
Analyze evaluation results and close the loop. Specification failures create local CDRs to fix agent rules; generalization failures go to evaluator backlog.
evals-clarify
Refine, cluster, and accept draft criteria into the published goldset. Isolates 20% holdout split and publishes goldset.md + goldset.json.
evals-implement
Generate executable graders and configs from goldset. Generates Python graders / metrics and auto-runs unit tests to verify grader correctness.
evals-init
Initialize evals/{system}/ directory structure for evaluation system following EDD principles (Standalone). Choose PromptFoo or DeepEval based on tech stack, generate security baseline.
evals-specify
Extract eval criteria from product specs and production failure traces (bottom-up error analysis). Writes proposed criteria to .adlc/drafts/evals/.
evals-validate
Run evaluations and validate evaluator quality (SLA compliance, TPR/TNR, statistical accuracy). Executes PromptFoo or pytest DeepEval.
product-analyze
Read-only analysis of PDR↔PRD consistency, PDR quality, cross-PDR conflicts, and staleness. Outputs a structured markdown report with severity-assigned findings. Use after /product-implement or periodically to detect drift.
product-clarify
Refine and validate Product Decision Records through targeted clarification questions. Review PDR completeness, detect conflicts, approve decisions, and update status to Accepted. Use before /product-implement.
product-implement
Generate a full Product Requirements Document (PRD.md) from accepted PDRs using multi-agent DAG orchestration. Reads individual PDR files, generates PRD sections from templates, validates output, and promotes accepted PDRs to memory. Use after /product-clarify.
product-init
Reverse-engineer Product Decision Records (PDRs) from an existing codebase and documentation using multi-agent feature-area analysis (brownfield). Use when documenting product decisions inferred from an already-built product.
product-specify
Interactive PRD exploration and Product Decision Record (PDR) creation for greenfield products. Facilitates product discovery discussions, surfaces trade-offs, and documents decisions as individual PDR files. Use when starting a new product or major pivot.
team-constitution
Interactively create or amend the team constitution in team-ai-directives. Use when bootstrapping a new team AI directives, establishing team-wide principles for the first time, or amending existing ones.
team-discover
Manually re-scan team context modules and produce a structured discovery table with relevance assessments. The CDR index is already in the system prompt; use this for explicit re-discovery.
team-repair
Re-index OKF v0.2 index.md/log.md files, derive CDR.md, rebuild .skills.json and AGENTS.md in team-ai-directives, migrate v0.1→v0.2 frontmatter, scan for rule conflicts, and verify directive freshness. Use when indexes are inconsistent, orphans are detected, after bulk changes, o
team-setup
Interactive setup of team AI directives. Use when bootstrapping a team directives repository from scratch, cloning an existing one, pointing to a local path, or checking an existing configuration. Auto-invoked by team-boot when a project has no configured team AI directives (self
team-skills
Browse and install team skills from the team AI directives. Use when listing, adding, or onboarding team skills to the current agent's skills directory. Supports --all to install every default and external skill at once.