Optimization Suggest

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-insights/skills/optimization-suggestThe 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: Suggest concrete optimizations for Claude Code usage based on historical session data. Covers cost reduction, speed improvement, error prevention, and workflow efficiency. Use for data-driven optimization planning.

---
name: optimization-suggest
description: >
  Suggest concrete optimizations for Claude Code usage based on historical
  session data. Covers cost reduction, speed improvement, error prevention,
  and workflow efficiency. Use for data-driven optimization planning.
---

# Optimization Suggest

Generate data-driven optimization recommendations for Claude Code usage.

## Input

The user provides: **$ARGUMENTS**

This may be:
- "all" or empty (default: comprehensive optimization scan)
- "cost" for cost reduction focus
- "speed" for performance/speed focus
- "quality" for error reduction focus
- "efficiency" for workflow efficiency focus

## Procedure

1. **Gather optimization data** from `http://localhost:4820`:
   - `GET /api/sessions?limit=200` — session history
   - `GET /api/analytics` — tool and token analytics
   - `GET /api/pricing/cost` — cost data
   - `GET /api/pricing` — pricing rules for model comparison
   - Sample event streams for behavioral analysis

2. **Analyze optimization opportunities**:

   ### 💰 Cost Optimization
   - **Model downgrade opportunities**: Tasks completed with expensive models that could use cheaper ones
     - Compare success rates per model per task type
     - Calculate savings from model substitution
   - **Cache optimization**: Sessions with low cache hit rates
     - Identify sessions that could benefit from better prompt caching
   - **Early termination**: Sessions that ran longer than needed
     - Detect sessions where useful work completed well before session end
   - **Compaction reduction**: Sessions hitting context limits
     - Suggest breaking large tasks into smaller sessions

   ### ⚡ Speed Optimization
   - **Tool selection**: Faster alternatives for commonly-used tool patterns
   - **Subagent parallelization**: Tasks that could run in parallel
   - **Session planning**: Better upfront context to reduce back-and-forth
   - **Preemptive context loading**: Frequently needed files/context

   ### 🛡 Quality Optimization
   - **Error prevention**: Common error patterns with preventive measures
   - **Tool reliability**: Tools with high failure rates and alternatives
   - **Validation gaps**: Sessions lacking verification steps
   - **Recovery strategies**: Better error handling patterns

   ### 🔄 Workflow Optimization
   - **Session sizing**: Optimal session scope based on historical success
   - **Task decomposition**: Complex sessions that should be split
   - **Automation candidates**: Repetitive workflows to automate
   - **Knowledge reuse**: Patterns where previous session context could help

3. **Quantify each recommendation**:
   - Estimated impact (cost savings $, time savings %, error reduction %)
   - Implementation effort (low/medium/high)
   - Confidence level based on data available
   - Priority score = Impact × Confidence / Effort

## Output Format

Present as a prioritized optimization plan:

| # | Recommendation | Category | Impact | Effort | Priority |
|---|---------------|----------|--------|--------|----------|
| 1 | Specific action | 💰/⚡/🛡/🔄 | High | Low | ★★★★★ |
| 2 | Specific action | ... | ... | ... | ★★★★☆ |

For the top 5 recommendations, include:
- Detailed explanation with supporting data
- Step-by-step implementation guide
- Expected before/after metrics
- How to measure success

Excerpt, first 3,320 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 Optimization Suggest

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

Spotted something wrong? Report a correction · Methodology