contract-manifest
Generate a human-readable manifest for an AIWG skill chain — agent assignments, requires/ensures contracts, data flow, and parallelization opportunities.
What this skill does
# Contract Manifest Skill
Generate a manifest showing how a chain of AIWG skills connects — mapping each skill's `ensures:` outputs to the next skill's `requires:` inputs.
## Triggers
- "show the contract manifest for [skill1] → [skill2] → [skill3]"
- "how does [workflow] wire together?"
- "generate manifest for this skill chain"
- "show data flow for [issue-planner] → [address-issues]"
- "what does [skill] produce and what does [skill] need?"
## Parameters
### Skills list (positional)
Ordered list of skill names or paths:
```bash
/contract-manifest issue-planner address-issues
/contract-manifest prose-detect prose-run forme-manifest
```
### `--workflow <file>` (optional)
Path to a YAML workflow definition:
```yaml
# workflow.yaml
name: Issue Planning Pipeline
steps:
- skill: issue-planner
- skill: address-issues
- skill: issue-sync
```
### `--mermaid` (optional)
Include a Mermaid LR diagram of the skill chain.
### `--json` (optional)
Output the manifest as machine-readable JSON instead of Markdown.
## Behavior
### Step 1: Resolve Skills
For each skill name, find the canonical `SKILL.md`:
1. Check `agentic/code/frameworks/sdlc-complete/skills/{name}/SKILL.md`
2. Check `agentic/code/addons/*/skills/{name}/SKILL.md`
3. Check `.claude/skills/{name}/SKILL.md`
4. If path given directly: read that file
### Step 2: Extract Contracts
From each skill's YAML frontmatter, extract:
- `requires:` — inputs the skill needs
- `ensures:` — outputs the skill commits to deliver
- `errors:` — failure conditions
- `invariants:` — always-true properties
If a skill has no contract fields, note it as "contract not yet defined."
### Step 3: Build Wiring Table
For each skill's `requires:` entry, find the upstream source:
1. **Exact match**: Another skill's `ensures:` entry with the same name → **direct wire** ✓
2. **Semantic match**: Another skill's `ensures:` entry that means the same thing (e.g., `issues-filed` ↔ `issues`) → **semantic wire** ⚠️ (flag as warning)
3. **External input**: The workflow's own `requires:` (user provides it) → **external** →
4. **No match**: Nothing upstream provides it → **unresolved** ❌
### Step 4: Determine Execution Order
- Skills with only external inputs can execute first
- Skills depending on upstream `ensures:` must wait for that skill
- Skills with no dependencies between them can execute in parallel
### Step 5: Output Manifest
```markdown
## Contract Manifest: {workflow name or skill list}
### Skills
| Skill | Requires | Ensures | Errors |
|-------|----------|---------|--------|
| issue-planner | objective, tracker | issues-filed, research-brief | no-tracker-access, research-failed |
| address-issues | issues, tracker | cycle-comments, aggregate-report | tracker-unavailable |
### Data Flow
| Source Skill | Output | → | Target Skill | Input | Match |
|-------------|--------|---|-------------|-------|-------|
| (external) | objective | → | issue-planner | objective | ✓ exact |
| issue-planner | issues-filed | → | address-issues | issues | ⚠️ semantic |
| issue-planner | tracker | → | address-issues | tracker | ✓ exact |
### Execution Order
1. issue-planner (requires: external inputs only)
2. address-issues (requires: issue-planner.issues-filed, issue-planner.tracker)
**Parallel groups**: [issue-planner] → [address-issues]
### Warnings
- `issue-planner.issues-filed` → `address-issues.issues`: semantic match only (names differ; verify intent)
### Issues
- None
```
### Optional: Mermaid Diagram (`--mermaid`)
```mermaid
graph LR
Input[External Input] --> A[issue-planner]
A -->|issues-filed| B[address-issues]
A -->|tracker| B
B --> Output[Aggregate Report]
```
## Output Formats
| Flag | Format | Use Case |
|------|--------|----------|
| (default) | Markdown | Human review |
| `--json` | JSON | Tooling, CI integration |
| `--mermaid` | Markdown + embedded Mermaid | Documentation |
## Model
Runs on **Sonnet** — contract extraction and matching is structural analysis.
## References
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/README.md — SDLC framework context and skill catalog
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/research-before-decision.md — Research-first approach for contract resolution
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/diagram-generation.md — Mermaid diagram generation standards
- @$AIWG_ROOT/docs/extensions/overview.md — Extension system and skill architecture
- @$AIWG_ROOT/docs/cli-reference.md — CLI reference
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.