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Agents Analyze

  • 55 installs
  • 49 repo stars
  • Updated August 4, 2026
  • laurigates/claude-plugins

Helps with ai & agent building tasks.

About

agents-analyze is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • agents-analyze
  • AI & Agent Building
  • AI-coding skill

Agents Analyze by the numbers

  • 55 all-time installs (skills.sh)
  • Ranked #6,762 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/laurigates/claude-plugins --skill agents-analyze

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Listed on Skillselion
Installs55
repo stars49
Last updatedAugust 4, 2026
Repositorylaurigates/claude-plugins

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

/agents:analyze

Analyze the plugin collection to identify where sub-agents would improve workflows by isolating verbose output, enforcing constraints, or specializing behavior.

When to Use This Skill

Use this skill when...Use a sibling skill instead when...
Auditing the whole plugin collection for sub-agent opportunities (verbose-output skills, model mismatches, tool over-permissions)Auditing a single agent's frontmatter, tool list, and prompt completeness — use agent-patterns-plugin:meta-audit
Mapping delegation gaps and producing a list of proposed new agentsAuthoring the new agent file from that proposal — use agent-patterns-plugin:custom-agent-definitions
Confirming every agent runs on Opus (the always-Opus standard)Configuring an agent's hooks, permissions, or settings.json wiring — use hooks-plugin:hooks-configuration
Focusing the analysis on a single plugin's skills (--focus <plugin>)Coordinating multiple agents at runtime — use agent-patterns-plugin:agent-teams or parallel-agent-dispatch

Agentic Optimizations

ContextCommand
List all pluginsfind . -maxdepth 1 -type d -name '*-plugin'
Count skills per plugin`find <plugin>/skills -name 'SKILL.md' -o -name 'skill.md' \
List existing agentsfind agents-plugin/agents -maxdepth 1 -name '*.md'
Check agent model fieldgrep -r '^model:' agents-plugin/agents/
Check agent allowed-toolsgrep -r '^allowed-tools:' agents-plugin/agents/
Skill tool permissionsgrep -r '^allowed-tools:' */skills/*/SKILL.md

Context

  • Plugin directories: !find . -maxdepth 1 -type d -name '*-plugin'
  • Existing agents: !find . -path '*/agents-plugin/agents/*' -maxdepth 3 -name '*.md'
  • Skills: !find . -path '*/skills/*/skill.md'
  • Skills (user-invocable): !find . -path '*/skills/*/SKILL.md' -not -path './agents-plugin/*'

Parameters

  • $1: Optional --focus <plugin-name> to analyze a single plugin in depth

Your Task

Perform a systematic analysis of the plugin collection to identify sub-agent opportunities.

Step 1: Inventory Current State

Scan the repository to build an inventory:

1. List all plugins with their skill/command counts 2. Read existing agents in agents-plugin/agents/ to understand current coverage 3. If `--focus` is provided, restrict analysis to that plugin only

Step 2: Identify Sub-Agent Opportunities

For each plugin (or focused plugin), evaluate skills and commands against these criteria:

Context Isolation (Primary Value)

Operations that produce verbose output benefiting from isolation:

IndicatorExamples
Build toolsdocker build, cargo build, webpack, tsc
Infrastructure opsterraform plan/apply, kubectl describe
Test runnersFull test suite output, coverage reports
Profiling toolsFlame graphs, benchmark results
Security scannersVulnerability reports, audit output
Log analysisApplication logs, system logs
Package managersDependency trees, audit results
Constraint Enforcement

Operations that should be limited to specific tools:

ConstraintRationale
Read-only analysisSecurity audit, code review - no writes
No networkPure code analysis tasks
Limited bashTasks that shouldn't execute arbitrary commands
Model: Always Opus

Every plugin agent runs on model: opus. A subagent's output re-enters the main loop as a tool result, so a weaker delegate quietly degrades everything downstream — and Opus-low beats Sonnet-high on both quality and tokens. So `effort` (a session setting), not `model`, is the cost lever: a mechanical agent stays on Opus and dials effort down rather than downgrading the model.

Audit findingRecommendation
Agent file declares model: opusOK — no change
Agent file declares sonnet / haiku / any non-opusFlag it — recommend model: opus, and note that mechanical agents tune effort down instead
Agent file omits model:Flag it — agents require an explicit model: opus

The sole sanctioned non-Opus subagent is the agent-patterns-plugin:cold-read-gate haiku reader, which is a skill-inline Agent(model: haiku) dispatch (the measurement instrument), not an agent file — so no */agents/*.md is exempt. The scripts/check-agent-model.sh lint enforces this; see .claude/rules/agent-development.md § "Model Selection for Agents".

Step 3: Gap Analysis

Compare identified opportunities against existing agents:

1. Missing agents: Skills that have no corresponding agent 2. Non-opus agents: Any agent file not on model: opus (always-Opus standard) 3. Tool over-permissions: Agents with tools they don't need 4. Consolidation opportunities: Multiple agents that could be merged 5. Delegation mapping: Check if /delegate references agents that don't exist

Step 4: Produce Recommendations

For each recommended new agent, specify:

### Proposed: <agent-name>

- **Model**: opus (always; tune `effort` down for mechanical agents, never the model)
- **Covers plugins**: <list>
- **Context value**: <what verbose output it isolates>
- **Tools**: <minimal set>
- **Constraint**: <read-only, no-network, etc.>
- **Priority**: HIGH | MEDIUM | LOW
- **Rationale**: <why this is better than inline execution>

For model/tool corrections to existing agents:

### Fix: <agent-name>

- **Current model**: <non-opus> → **Recommended**: opus (then dial `effort` down if mechanical)
- **Reason**: <why the change improves things — e.g. restores the always-Opus standard>

Step 5: Implementation Check

If new agents are recommended, check:

  • [ ] Agent name doesn't conflict with existing
  • [ ] Agent fills a gap referenced by /delegate command
  • [ ] Model is opus (always-Opus standard; effort is the cost lever, not the model)
  • [ ] Tool set is minimal (principle of least privilege)
  • [ ] Agent has clear "does / does NOT do" boundaries

Output Format

## Sub-Agent Analysis Report

**Scope**: [All plugins | focused plugin name]
**Date**: [today]
**Plugins analyzed**: N
**Existing agents**: N
**Skills without agent coverage**: N

### Current Coverage Map

| Domain | Agent | Skills Covered | Gaps |
|--------|-------|----------------|------|
| ... | ... | ... | ... |

### Recommended New Agents

[Proposals from Step 4]

### Recommended Fixes

[Model/tool corrections from Step 4]

### Delegation Mapping Updates

[Any updates needed for /delegate command's agent reference table]

### Priority Summary

| Priority | Count | Top Recommendation |
|----------|-------|-------------------|
| HIGH | N | ... |
| MEDIUM | N | ... |
| LOW | N | ... |

Post-Actions

After presenting the analysis: 1. Ask the user if they want to implement any of the recommendations 2. If yes, create the agent files following the existing patterns in agents-plugin/agents/ 3. Update agents-plugin/README.md with new agents 4. Update /delegate command's agent reference table if needed

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