agent-code-goal-planner
Agent skill for code-goal-planner - invoke with $agent-code-goal-planner
Install with Tessl CLI
npx tessl i github:ruvnet/claude-flow --skill agent-code-goal-planner42
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 89%
↑ 2.28xAgent success when using this skill
Validation for skill structure
Evaluation results
98%
44%Notification Service Implementation Plan
SPARC-GOAP feature implementation planning
Specification phase present
66%
100%
Pseudocode phase present
0%
71%
Architecture phase present
57%
100%
Refinement phase present
42%
100%
Completion phase present
85%
100%
claude-flow sparc commands
0%
100%
Milestone id field
100%
100%
Milestone preconditions field
100%
100%
Milestone deliverables field
100%
100%
Milestone success_criteria field
0%
100%
Milestone estimated_hours field
0%
100%
Milestone dependencies field
60%
100%
Milestone SPARC phase mapping
25%
100%
Risk assessment technical dimension
100%
100%
Risk assessment multi-dimensional
85%
100%
Definition of done
100%
100%
Without context: $0.2998 · 2m · 12 turns · 16 in / 7,126 out tokens
With context: $0.5830 · 2m 58s · 18 turns · 277 in / 10,336 out tokens
71%
32%Engineering Health Dashboard: Current State vs Target State Analysis
GOAP state analysis with quality metrics
current_state object
50%
100%
goal_state object
50%
100%
test_coverage field
100%
100%
tech_debt field
0%
100%
bugs_open field
100%
100%
Coverage target >= 80%
0%
100%
Complexity target < 10
100%
100%
Duplication target < 3%
0%
100%
p99 latency target
0%
0%
Throughput target
0%
0%
Error rate target
0%
50%
MTTR target
100%
100%
Test pyramid breakdown
0%
20%
Milestone state transitions
100%
100%
Without context: $0.3162 · 2m 19s · 11 turns · 16 in / 7,590 out tokens
With context: $0.6959 · 3m 21s · 22 turns · 441 in / 10,841 out tokens
100%
75%Automated Multi-Agent Development Workflow Setup
MCP tool integration for development swarm
swarm_init call
37%
100%
swarm_init topology
0%
100%
swarm_init maxAgents
28%
100%
agent_spawn call
25%
100%
sparc-coder agent type
0%
100%
sparc-coder capabilities
0%
100%
task_orchestrate call
25%
100%
task_orchestrate strategy
0%
100%
memory_usage store call
0%
100%
memory namespace code-patterns
0%
100%
Sequential ordering
66%
100%
Inline comments
100%
100%
Without context: $0.3114 · 2m 4s · 11 turns · 14 in / 7,376 out tokens
With context: $0.5349 · 2m 13s · 21 turns · 388 in / 7,750 out tokens
- Evaluated
- Agent
- Claude Code
- Model
- Unknown
Table of Contents
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