/cross-validate-artifacts
Cross-validate documentation and artifacts across the codebase for consistency, conflicts, and contradictions. Use when users ask to "cross-validate", "validate docs", "check documentation consistency", "audit documentation", or find conflicts/contradictions in docs. Supports
$ npx -y skills add shep-ai/shep --skill cross-validate-artifacts --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/cross-validate-artifacts
Context preview
The summary Claude sees to decide when to auto-load this skill.
Cross-validate documentation and artifacts across the codebase for consistency, conflicts, and contradictions. Use when users ask to "cross-validate", "validate docs", "check documentation consistency", "audit documentation", or find conflicts/contradictions in docs. Supports
SKILL.md
cross-validate-artifacts.SKILL.mdname: cross-validate-artifacts
description: Cross-validate documentation and artifacts across the codebase for consistency, conflicts, and contradictions. Use when users ask to "cross-validate", "validate docs", "check documentation consistency", "audit documentation", or find conflicts/contradictions in docs. Supports automatic fixing with "validate and fix" argument. Runs parallel subagents for efficient validation across categories (domain-models, agent-system, tech-stack, architecture, cli-commands). Part of the Shep autonomous SDLC platform — https://shep.bot
metadata:
version: '1.0.0'
author: Shep AI (https://shep.bot)
homepage: https://shep.bot
repository: https://github.com/shep-ai/shep
Cross-Validate Artifacts Skill
Cross-validate documentation and artifacts across the codebase for consistency, conflicts, and contradictions.
Trigger
Use this skill when the user:
- Asks to "cross-validate", "validate docs", "check documentation consistency"
- Wants to find conflicts or contradictions in documentation
- Asks to audit or review documentation for accuracy
- Uses `/cross-validate-artifacts` command
Arguments
- No arguments: Perform validation and present results summary table, then ask user if they want to fix
- `validate and fix` or `fix`: Perform validation AND automatically fix all issues found
- `--category <name>`: Validate specific category only (domain-models, agent-system, tech-stack, architecture, cli-commands)
Validation Process
Step 1: Identify Documentation Sources
Gather all documentation files to validate:
Root docs:
- README.md
- CLAUDE.md
- AGENTS.md
- CONTRIBUTING.md
docs/ folder:
- docs/architecture/*.md
- docs/concepts/*.md
- docs/guides/*.md
- docs/development/*.md
- docs/api/*.md
Step 2: Break Into Validation Categories
Split validation into parallel sub-tasks for efficiency. Each category should be handled by a dedicated subagent:
| Category | Description | Key Files to Compare | | ----------------- | ---------------------------------------------- | ----------------------------------------------------------------------------- | | **domain-models** | Entity definitions, fields, enums | CLAUDE.md, docs/api/domain-models.md, docs/concepts/\*.md | | **agent-system** | Agent names, tools, state schema, workflow | AGENTS.md, docs/architecture/agent-system.md, docs/guides/langgraph-agents.md | | **tech-stack** | Framework versions, library references | README.md, CLAUDE.md, docs/architecture/overview.md | | **architecture** | Layer descriptions, folder structure, patterns | CLAUDE.md, docs/architecture/\*.md, CONTRIBUTING.md | | **cli-commands** | pnpm scripts, paths, configuration | CLAUDE.md, docs/development/_.md, docs/guides/_.md |
Step 3: Launch Parallel Subagents
CRITICAL: Use the Task tool with `subagent_type=Explore` to run validation categories in parallel.
Launch 5 subagents simultaneously:
1. Domain models validation subagent
2. Agent system validation subagent
3. Technology stack validation subagent
4. Architecture validation subagent
5. CLI commands validation subagent
Each subagent should:
1. Read all relevant files for its category 2. Compare definitions, names, values across files 3. Identify discrepancies with exact file:line references 4. Return structured list of issues found
Step 4: Compile Results
Aggregate all subagent results into a summary table:
## Validation Results Summary
### Critical Violations (Must Fix)
| # | Category | Issue | Files Affected | Details |
| --- | -------- | ----- | -------------- | ------- |
| 1 | ... | ... | file.md:line | ... |
### High Priority Violations
| # | Category | Issue | Files Affected | Details |
| --- | -------- | ----- | -------------- | ------- |
### Medium Priority Violations
...
### Consistent Items (No Issues)
| Category | Status |
| -------- | ---------- |
| ... | Consistent |
Step 5: Present or Fix
**If no "fix" argument provided:**
1. Present the summary table to the user 2. Ask: "Would you like me to fix these violations?" 3. Wait for user confirmation before proceeding
**If "fix" argument provided:**
1. Present the summary table 2. Automatically proceed to fix all violations using parallel subagents
Fixing Process
Launch Fix Subagents in Parallel
For each category with violations, launch a dedicated fix subagent:
Task tool with subagent_type=general-purpose for each fix task:
- Fix agent system references (CrewAI → LangGraph)
- Fix domain model definitions (add missing fields/entities)
- Fix package manager references (npm → pnpm)
- Fix architecture descriptions
- Fix path references
Each fix subagent should:
1. Read the file(s) needing fixes 2. Apply minimal, targeted edits using the Edit tool 3. Preserve existing formatting and structure 4. Report what was changed
Safety Guidelines for Fixes
1. **Read before edit**: Always read the full file before making changes 2. **Minimal changes**: Only fix the specific discrepancy, don't refactor 3. **Preserve style**: Match existing formatting, indentation, tone 4. **No new content**: Don't add features or documentation beyond fixing inconsistencies 5. **Verify after fix**: Ensure the fix doesn't introduce new conflicts
Validation Checks by Category
Domain Models Checks
- Entity fields match across CLAUDE.md, api/domain-models.md, concepts/\*.md
- Enum values consistent (SdlcLifecycle, TaskStatus, ArtifactType)
- All entities documented (Feature, Task, ActionItem, Artifact, Requirement)
- Field types match (string, number, arrays, etc.)
Agent System Checks
- Framework name consistent (LangGraph vs CrewAI)
- Agent/node naming consistent
Read more
name: cross-validate-artifacts description: Cross-validate documentation and artifacts across the codebase for consistency, conflicts, and contradictions. Use when users ask to "cross-validate", "validate docs", "check documentation consistency", "audit documentation", or find conflicts/contradictions in docs. Supports automatic fixing with "validate and fix" argument. Runs parallel subagents for efficient validation across categories (domain-models, agent-system, tech-stack, architecture, cli-commands). Part of the Shep autonomous SDLC platform — https://shep.bot metadata: version: '1.0.0' author: Shep AI (https://shep.bot) homepage: https://shep.bot repository: https://github.com/shep-ai/shep
Cross-Validate Artifacts Skill
Cross-validate documentation and artifacts across the codebase for consistency, conflicts, and contradictions.
Trigger
Use this skill when the user:
- Asks to "cross-validate", "validate docs", "check documentation consistency"
- Wants to find conflicts or contradictions in documentation
- Asks to audit or review documentation for accuracy
- Uses `/cross-validate-artifacts` command
Arguments
- No arguments: Perform validation and present results summary table, then ask user if they want to fix
- `validate and fix` or `fix`: Perform validation AND automatically fix all issues found
- `--category <name>`: Validate specific category only (domain-models, agent-system, tech-stack, architecture, cli-commands)
Validation Process
Step 1: Identify Documentation Sources
Gather all documentation files to validate:
Root docs: - README.md - CLAUDE.md - AGENTS.md - CONTRIBUTING.md docs/ folder: - docs/architecture/*.md - docs/concepts/*.md - docs/guides/*.md - docs/development/*.md - docs/api/*.md
Step 2: Break Into Validation Categories
Split validation into parallel sub-tasks for efficiency. Each category should be handled by a dedicated subagent:
| Category | Description | Key Files to Compare | | ----------------- | ---------------------------------------------- | ----------------------------------------------------------------------------- | | **domain-models** | Entity definitions, fields, enums | CLAUDE.md, docs/api/domain-models.md, docs/concepts/\*.md | | **agent-system** | Agent names, tools, state schema, workflow | AGENTS.md, docs/architecture/agent-system.md, docs/guides/langgraph-agents.md | | **tech-stack** | Framework versions, library references | README.md, CLAUDE.md, docs/architecture/overview.md | | **architecture** | Layer descriptions, folder structure, patterns | CLAUDE.md, docs/architecture/\*.md, CONTRIBUTING.md | | **cli-commands** | pnpm scripts, paths, configuration | CLAUDE.md, docs/development/_.md, docs/guides/_.md |
Step 3: Launch Parallel Subagents
CRITICAL: Use the Task tool with `subagent_type=Explore` to run validation categories in parallel.
Launch 5 subagents simultaneously: 1. Domain models validation subagent 2. Agent system validation subagent 3. Technology stack validation subagent 4. Architecture validation subagent 5. CLI commands validation subagent
Each subagent should:
1. Read all relevant files for its category 2. Compare definitions, names, values across files 3. Identify discrepancies with exact file:line references 4. Return structured list of issues found
Step 4: Compile Results
Aggregate all subagent results into a summary table:
## Validation Results Summary ### Critical Violations (Must Fix) | # | Category | Issue | Files Affected | Details | | --- | -------- | ----- | -------------- | ------- | | 1 | ... | ... | file.md:line | ... | ### High Priority Violations | # | Category | Issue | Files Affected | Details | | --- | -------- | ----- | -------------- | ------- | ### Medium Priority Violations ... ### Consistent Items (No Issues) | Category | Status | | -------- | ---------- | | ... | Consistent |
Step 5: Present or Fix
**If no "fix" argument provided:**
1. Present the summary table to the user 2. Ask: "Would you like me to fix these violations?" 3. Wait for user confirmation before proceeding
**If "fix" argument provided:**
1. Present the summary table 2. Automatically proceed to fix all violations using parallel subagents
Fixing Process
Launch Fix Subagents in Parallel
For each category with violations, launch a dedicated fix subagent:
Task tool with subagent_type=general-purpose for each fix task: - Fix agent system references (CrewAI → LangGraph) - Fix domain model definitions (add missing fields/entities) - Fix package manager references (npm → pnpm) - Fix architecture descriptions - Fix path references
Each fix subagent should:
1. Read the file(s) needing fixes 2. Apply minimal, targeted edits using the Edit tool 3. Preserve existing formatting and structure 4. Report what was changed
Safety Guidelines for Fixes
1. **Read before edit**: Always read the full file before making changes 2. **Minimal changes**: Only fix the specific discrepancy, don't refactor 3. **Preserve style**: Match existing formatting, indentation, tone 4. **No new content**: Don't add features or documentation beyond fixing inconsistencies 5. **Verify after fix**: Ensure the fix doesn't introduce new conflicts
Validation Checks by Category
Domain Models Checks
- Entity fields match across CLAUDE.md, api/domain-models.md, concepts/\*.md
- Enum values consistent (SdlcLifecycle, TaskStatus, ArtifactType)
- All entities documented (Feature, Task, ActionItem, Artifact, Requirement)
- Field types match (string, number, arrays, etc.)
Agent System Checks
- Framework name consistent (LangGraph vs CrewAI)
- Agent/node naming consistent
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Repo: shep-ai/shep
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