Workflow Optimizer

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 1f059c400d07 · 16 Oct 2026Report an issue or request a re-scan

• Publisherhoangsonww GitHub userOwner of the repository this skill is read from
• Source folderhoangsonww/Claude-Code-Agent-Monitor/plugins/ccam-productivity/skills/workflow-optimizerThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdict1f059c400d07A new audit runs when the source changes
• Repository statusNot archivedLast push 4 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Analyze workflow patterns using the Agent Monitor's workflow intelligence API — orchestration DAGs, tool flow transitions, subagent effectiveness, model delegation patterns, error propagation by depth, concurrency…

---
name: workflow-optimizer
description: >
  Analyze workflow patterns using the Agent Monitor's workflow intelligence
  API — orchestration DAGs, tool flow transitions, subagent effectiveness,
  model delegation patterns, error propagation by depth, concurrency lanes,
  compaction impact, and agent co-occurrence. Produces prioritized optimization
  recommendations with quantified impact.
---

# Workflow Optimizer

Analyze Claude Code workflows using the Agent Monitor's workflow intelligence engine.

## Input

The user provides: **$ARGUMENTS**

Options: "analyze", a session ID for single-session analysis, or a focus: "tools", "subagents", "cost", "errors".

## Data Sources

| Endpoint | Returns |
|----------|---------|
| `GET /api/sessions?limit=100` | Session list with metadata |
| `GET /api/workflows/{sessionId}` | **11 workflow datasets** (see below) |
| `GET /api/analytics` | Tool usage top 20, event types, agent types |
| `GET /api/pricing` | Model pricing rules for cost comparison |

### Workflow Intelligence API (`GET /api/workflows/{sessionId}`)

Returns these 11 datasets per session:

| Dataset | Content |
|---------|---------|
| `stats` | Aggregate session stats: tool count, agent depth, event count |
| `orchestration` | **DAG**: agent nodes with parent/child edges, depths, types |
| `toolFlow` | **Transition matrix**: tool A → tool B with counts (common sequences) |
| `effectiveness` | **Subagent success**: per-type completion rates, avg duration, task success |
| `patterns` | **Recurring sequences**: detected workflow patterns with frequency |
| `modelDelegation` | **Model choices**: which models are delegated which tasks |
| `errorPropagation` | **Error flow by depth**: where in the agent tree errors originate and propagate |
| `concurrency` | **Concurrency lanes**: overlapping agent execution timelines |
| `complexity` | **Complexity score**: numerical score based on depth, breadth, tool diversity |
| `compaction` | **Compaction impact**: token savings, frequency, context health |
| `cooccurrence` | **Agent pairs**: which agents frequently run together |

## Optimization Analyses

### 1. Tool Flow Optimization
From `toolFlow` transition data:
- Identify the most common tool sequences (e.g., Read → Edit → Bash)
- Find redundant transitions (same tool called repeatedly = retries)
- Detect anti-patterns: high-frequency failure loops
- Recommend tool chain shortcuts

### 2. Subagent Strategy
From `effectiveness` + `orchestration`:
- Which subagent types (task, explore, code-review) have highest completion rates
- Average duration per subagent type — are subagents taking too long?
- Underutilized types: tasks that could benefit from delegation
- Over-spawning: too many subagents for simple tasks

### 3. Model Delegation Analysis
From `modelDelegation`:
- Which models handle which task types
- Cost-per-task comparison across models
- Opportunities to delegate simple tasks to cheaper models (Haiku/Sonnet instead of Opus)
- Calculate estimated savings from model rebalancing

### 4. Error Prevention
From `errorPropagation`:
- Where errors originate (agent depth level)
- How errors cascade to parent agents
- Error types (APIError, tool failure) by frequency
- Defensive strategies: which patterns lead to fewer errors

### 5. Concurrency Optimization
From `concurrency`:
- Which agents run in parallel vs sequential
- Bottlenecks: sequential agents that could be parallelized
- Resource contention: overlapping heavy tasks

### 6. Context Health
From `compaction`:
- How often compaction occurs per session
- Token recovery from compaction baselines
- Sessions that hit context limits — suggest breaking into smaller tasks

## Output

Prioritized recommendations table:

| # | Recommendation | Source Data | Impact | Effort | Est. Savings |
|---|---------------|-------------|--------|--------|-------------|

Top 5 recommendations with detailed explanation, supporting data from the workflow API, and implementation steps.

Excerpt, first 3,986 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

1. 2026-10-16
   ✓SAFE B 89 / 100

   first audit · source 1f059c400d07

Questions about Workflow Optimizer

• github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plug — the audited source at commit 1f059c400d07 and every finding aboveObserved · 16 Oct 2026

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