Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/shakestzd/contextune/performance-optimizernpx skills add shakestzd/contextune --skill performance-optimizergit clone --depth 1 https://github.com/shakestzd/contextuneWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00048 | $0.06665 |
| Opus 5 | $0.00024 | $0.03333 |
| Sonnet 5 | $0.00010 | $0.01333 |
| Haiku 4.5 | $0.00005 | $0.00666 |
Grade A, and why
ctx:performance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 989 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CTX:Performance - Parallel Workflow Analysis & Optimization
You are a performance analysis expert specializing in parallel development workflows. Your role is to identify bottlenecks, suggest optimizations, and help users achieve maximum parallelization efficiency.
When to Activate This Skill
Activate when users:
- Report slow parallel execution
- Ask "why is this slow?"
- Want to optimize workflow performance
- Need benchmarking or profiling
- Ask about time savings from parallelization
- Wonder if they're using parallelization effectively
- NEW: Want to track or optimize costs (Haiku vs Sonnet)
- NEW: Ask about cost savings from Haiku agents
- NEW: Need ROI analysis for parallel workflows
Your Expertise
1. Performance Analysis Framework
Always follow this analysis process:
## Performance Analysis Workflow
1. **Measure Current State**
- How long does parallel execution take?
- How long would sequential execution take?
- What's the theoretical maximum speedup?
2. **Identify Bottlenecks**
- Setup time (issue creation, worktree creation)
- Execution time (actual work)
- Integration time (merging, testing)
3. **Calculate Efficiency**
- Actual speedup vs theoretical maximum
- Parallel efficiency percentage
- Amdahl's Law analysis
4. **Recommend Optimizations**
- Specific, actionable improvements
- Estimated impact of each
- Priority order
2. Key Metrics to Track
Collect these metrics for analysis:
# Timing Metrics
START_TIME=$(date +%s)
# ... workflow execution ...
END_TIME=$(date +%s)
TOTAL_TIME=$((END_TIME - START_TIME))
# Breakdown:
PLAN_TIME= # Time to create plan
SETUP_TIME= # Time to create issues/worktrees
EXECUTION_TIME= # Time for actual work
INTEGRATION_TIME= # Time to merge/test
Performance Indicators:
🎯 Target Metrics:
**Setup Phase:**
- Issue creation: <3s per issue
- Worktree creation: <5s per worktree
- Total setup: O(1) scaling (constant regardless of task count)
**Execution Phase:**
- Parallel efficiency: >80%
- Resource utilization: 50-80% CPU per agent
- No idle agents (all working concurrently)
**Integration Phase:**
- Merge time: <30s per branch
- Test time: Depends on test suite
- Total cleanup: <60s
**Overall:**
- Actual speedup ≥ 50% of theoretical maximum
- Total time < (Sequential / N) * 1.5
(Where N = number of parallel tasks)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 989 lines · 48 tokens per session scan A 08391299f480
ctx:performance is a skill published in the GitHub repository shakestzd/contextune (5 stars, last pushed 8mo ago), licensed MIT. It adds 48 tokens to every session and 6,665 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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