Best use case
agent-skill-bridge is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Teams using agent-skill-bridge should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/agent-skill-bridge/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent-skill-bridge Compares
| Feature / Agent | agent-skill-bridge | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
This skill provides specific capabilities for your AI agent. See the About section for full details.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Agent-Skill Integration Bridge
## Description
Facilitates seamless integration between Claude Skills and the existing Agent framework, enabling skills to invoke agents and vice versa with proper context handoffs.
## When to Use This Skill
- When creating a skill that needs to invoke an agent (Builder, Validator, etc.)
- When an agent needs to leverage a skill for specific workflow
- When orchestrating multi-agent workflows that include skills
- When troubleshooting agent-skill communication issues
## When NOT to Use This Skill
- For simple single-agent tasks (use agents directly)
- For simple single-skill tasks (use skills directly)
- When no integration is needed
## Prerequisites
- Understanding of agent framework (see agent templates)
- Understanding of skill architecture (see skill templates)
- Access to `MULTI_AGENT_PLAN.md` for orchestration
- Familiarity with both agent configs and SKILL.md formats
## Workflow
### Phase 1: Integration Planning
#### Step 1.1: Identify Integration Pattern
**Pattern A: Skill Invokes Agent**
```
User Request
↓
Skill (Primary workflow orchestrator)
↓
Agent (Specialized execution)
↓
Back to Skill (Result synthesis)
```
**Pattern B: Agent Invokes Skill**
```
User Request
↓
Agent (Primary workflow orchestrator)
↓
Skill (Specialized automation)
↓
Back to Agent (Continue workflow)
```
**Pattern C: Orchestrator Pattern**
```
User Request
↓
Orchestrator Skill
├→ Agent A (parallel)
├→ Agent B (parallel)
└→ Skill C (depends on A+B)
↓
Results Synthesis
```
#### Step 1.2: Define Handoff Protocol
Create handoff specification:
```
## Handoff Specification
**From**: [Skill/Agent Name]
**To**: [Agent/Skill Name]
**Trigger**: [When handoff occurs]
**Data Transfer:**
```json
{
"handoff_type": "skill_to_agent | agent_to_skill",
"source": "source-name",
"destination": "destination-name",
"context": {
"execution_id": "unique-id",
"phase": "current-phase",
"data": {
// Relevant data structure
}
},
"requirements": {
"agent_role": "builder | validator | scribe | devops | researcher",
"expected_output": "description of what agent should produce",
"quality_criteria": ["criterion1", "criterion2"]
}
}
```
**Return Path:**
```json
{
"source": "agent-name",
"destination": "skill-name",
"execution_id": "same-unique-id",
"status": "success | partial | failure",
"output": {
// Agent's produced artifact
},
"metadata": {
"duration": "execution-time",
"quality_score": "0-100",
"notes": ["note1", "note2"]
}
}
```
```
### Phase 2: Implementation
#### Step 2.1: Skill-to-Agent Invocation
**In SKILL.md, add agent invocation step:**
```
### Step X: Invoke [Agent Name] Agent
**Purpose**: [Why agent is needed]
**Agent Configuration:**
- **Role**: [builder | validator | scribe | devops | researcher]
- **Context Required**:
- [File 1]
- [File 2]
- [Variable: value]
**Invocation:**
Update `MULTI_AGENT_PLAN.md`:
```markdown
## Phase [N]: [Agent Name] Execution
**Agent**: [Agent Name] (see `.claude/agents/[agent].md`)
**Trigger**: [Skill Name] skill - Step X
**Input**: [What skill provides]
### Tasks for [Agent Name]:
1. [Task 1 with acceptance criteria]
2. [Task 2 with acceptance criteria]
### Expected Output:
[Detailed description]
### Return to Skill:
After completion, return results to [Skill Name] skill for [next step].
```
**Handoff Message:**
```markdown
---
TO: [Agent Name] Agent
FROM: [Skill Name] Skill
EXECUTION_ID: [skill-exec-id]
PHASE: [current-phase]
**Context Provided:**
- [Context item 1]: [Location/value]
- [Context item 2]: [Location/value]
**Tasks:**
1. [Task 1]
2. [Task 2]
**Acceptance Criteria:**
- [Criterion 1]
- [Criterion 2]
**Return Requirements:**
- Output format: [Specification]
- Handoff location: [Where to place results]
- Notification: Update MULTI_AGENT_PLAN.md when complete
**Questions/Blockers:**
Contact: [Skill maintainer]
---
```
**Wait for Agent Completion:**
- Monitor `MULTI_AGENT_PLAN.md` for status updates
- Agent marks tasks complete
- Results available at specified location
**Receive Results:**
```markdown
### Step X+1: Process [Agent Name] Results
Load agent output from [location]
Validate:
- [ ] Output format matches specification
- [ ] Acceptance criteria met
- [ ] No errors reported
IF validation passes:
Proceed to next step
ELSE:
Review issues and either:
- Request agent revision
- Adapt workflow
- Escalate to human
```
```
#### Step 2.2: Agent-to-Skill Invocation
**In agent config (e.g., `builder.md`), add skill invocation:**
```
## Workflow Pattern: Invoke [Skill Name] Skill
When [condition for skill invocation]:
1. **Prepare Skill Input:**
```markdown
Create skill-input.json:
{
"parameter1": "value1",
"parameter2": "value2",
"context": {
// Relevant context from agent
}
}
```
2. **Invoke Skill:**
Reference skill documentation: `skills/[skill-name]/SKILL.md`
Execute skill with: "Use [skill-name] skill with input from skill-input.json"
3. **Receive Skill Output:**
Skill produces: [expected output]
Validate:
- [ ] Output format correct
- [ ] Quality standards met
- [ ] Integration points clear
4. **Continue Agent Workflow:**
Use skill output to [next agent step]
```
### Phase 3: Orchestration
#### Step 3.1: Multi-Agent-Skill Orchestration
Create orchestrator configuration in `MULTI_AGENT_PLAN.md`:
```
# Multi-Agent-Skill Orchestration Plan
## Workflow: [Workflow Name]
**Orchestrator**: [Lead Skill or Lead Agent]
### Execution Graph:
```
Phase 1: [Orchestrator Skill] - Requirements Gathering
↓
Phase 2: [Architect Agent] - System Design (parallel with Phase 3)
↓ ↓
Phase 3: [Research Skill] Phase 4: [Builder Agent]
↓ ↓
Phase 5: [Orchestrator Skill] - Synthesis
↓
Phase 6: [Validator Agent] - Quality Assurance
↓
Phase 7: [PR-Generator Skill] - Finalization
```
### Phase Details:
#### Phase 1: [Orchestrator Skill] - Requirements
**Duration**: [X min]
**Output**: Requirements document
**Next**: Triggers Phase 2 and 3 in parallel
#### Phase 2: [Architect Agent] - Design
**Input**: Requirements document from Phase 1
**Tasks**:
- Create ARCHITECTURE.md
- Define component structure
**Output**: Architecture specification
**Next**: Triggers Phase 4
#### Phase 3: [Research Skill] - Technology Analysis
**Input**: Requirements document from Phase 1
**Tasks**:
- Research relevant technologies
- Generate comparison matrix
**Output**: Technology recommendations
**Next**: Merges with Phase 2 output for Phase 4
#### Phase 4: [Builder Agent] - Implementation
**Input**:
- Architecture spec from Phase 2
- Tech recommendations from Phase 3
**Tasks**:
- Implement feature
- Write tests
**Output**: Implemented code
**Next**: Triggers Phase 5
[Continue for all phases...]
### Handoff Protocol:
**Phase N → Phase N+1:**
```json
{
"from_phase": "N",
"to_phase": "N+1",
"handoff_data": {
"artifacts": ["artifact1.md", "artifact2.js"],
"context": {},
"status": "complete",
"quality_score": 95
}
}
```
```
## Examples
### Example 1: PR Description Skill → Validator Agent
**Scenario**: PR description skill generates description, needs code quality validation
**Integration:**
```
## PR Description Skill - Step 5: Request Validation
After generating PR description:
1. Create validation request:
```markdown
---
TO: Validator Agent
FROM: PR Description Skill
**Request**: Code quality validation for PR #123
**Files to Review:**
- src/auth/jwt.service.js
- tests/auth/jwt.test.js
**Focus Areas:**
- Test coverage ≥90%
- Security: Token validation
- Performance: No N+1 queries
**Return**: Validation report to `pr-123-validation.md`
---
```
2. Wait for validator completion
3. Receive validation results:
```markdown
## Validation Report: PR #123
**Status**: ✅ APPROVED
**Test Coverage**: 94%
**Security**: ✅ No issues
**Performance**: ✅ Optimized
**Recommendation**: Safe to merge
```
4. Append validation summary to PR description:
```markdown
## Quality Validation
✅ Automated validation passed
- Test coverage: 94%
- Security scan: Clean
- Performance: Optimized
Validated by: Validator Agent
Report: pr-123-validation.md
```
```
### Example 2: Builder Agent → Code Formatter Skill
**Scenario**: Builder implements code, needs consistent formatting applied
**Integration in builder.md:**
```
## After Code Implementation
### Step X: Apply Code Formatting
Instead of manual formatting commands, invoke skill:
1. Prepare context:
```json
{
"files_changed": ["src/**/*.js", "tests/**/*.js"],
"style_guide": ".eslintrc.json",
"formatter": "prettier"
}
```
2. Invoke: "Use code-formatter skill with context from above"
3. Skill returns:
```json
{
"status": "success",
"files_formatted": 12,
"issues_fixed": 45,
"remaining_issues": 0
}
```
4. Validate formatting:
```bash
npm run lint
```
5. Commit formatted code:
```bash
git add .
git commit -m "style: apply code formatter skill"
```
```
### Example 3: Orchestrator Skill Coordinating 3 Agents
**Scenario**: Feature development requiring Architect → Builder → Validator sequence
```
## Feature Implementation Orchestrator Skill
### Phase 2: Architecture Planning
**Invoke**: Architect Agent
**Handoff:**
```markdown
---
TO: Architect Agent
FROM: Feature Orchestrator Skill
FEATURE: User Authentication
**Requirements:**
- JWT-based authentication
- Refresh token support
- Rate limiting
- Session management
**Deliverables:**
- ARCHITECTURE.md: Auth system design
- SECURITY.md: Security model
- TECH_STACK.md: Libraries selected
**Timeline**: 2 hours
**Budget**: High priority
---
```
**Wait for**: Architect marks complete in MULTI_AGENT_PLAN.md
### Phase 3: Implementation
**Invoke**: Builder Agent
**Handoff:**
```markdown
---
TO: Builder Agent
FROM: Feature Orchestrator Skill
SOURCE: ARCHITECTURE.md from Phase 2
**Tasks:**
Implement auth system per architecture spec
**Acceptance:**
- All tests passing
- Code coverage ≥90%
- Follows ARCHITECTURE.md design
**Timeline**: 6 hours
---
```
**Wait for**: Builder marks complete
### Phase 4: Validation
**Invoke**: Validator Agent
**Handoff:**
```markdown
---
TO: Validator Agent
FROM: Feature Orchestrator Skill
PR: #456
**Review Focus:**
- Security validation
- Test coverage verification
- Performance benchmarking
**Acceptance:**
- Zero critical issues
- Coverage ≥90%
- Performance within targets
---
```
**Receive**: Validation report
### Phase 5: Synthesis
Orchestrator skill compiles:
- Architecture design
- Implementation code
- Validation results
- PR description
**Final Output**: Complete feature package ready for merge
```
## Quality Standards
- Handoffs must include unique execution_id for traceability
- All context required by recipient must be explicitly provided
- Return paths must be clearly defined
- Timeout handling for agent/skill execution
- Graceful degradation if agent/skill unavailable
## Common Pitfalls
### Pitfall 1: Missing Context in Handoff
**Issue**: Agent/skill fails because required context not provided
**Solution**: Always validate context completeness before handoff
```
## Pre-Handoff Checklist
- [ ] All required files accessible
- [ ] All parameters defined
- [ ] Acceptance criteria clear
- [ ] Return path specified
- [ ] Execution ID assigned
```
### Pitfall 2: No Timeout Handling
**Issue**: Waiting indefinitely for agent/skill completion
**Solution**: Implement timeout with fallback
```
### Step X: Invoke [Agent] with Timeout
1. Invoke agent
2. Set timeout: 30 minutes
3. IF timeout:
Log warning
Either:
- Use partial results
- Skip this step
- Request human intervention
```
### Pitfall 3: Circular Dependencies
**Issue**: Skill A calls Agent B which calls Skill A
**Solution**: Design clear dependency graph, avoid cycles
```
✅ GOOD:
Skill → Agent → Skill (different skill)
❌ BAD:
Skill A → Agent → Skill A (circular)
```
## Version History
- 1.0.0 (2025-11-22): Initial releaseRelated Skills
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