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.
git clone --depth 1 https://github.com/athola/claude-night-marketWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/athola/claude-night-market/context-optimizer)<a href="https://agentmods.dev/agents/athola/claude-night-market/context-optimizer"><img src="https://agentmods.dev/badge/agents/athola/claude-night-market/context-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/athola/claude-night-market/context-optimizer"><img src="https://agentmods.dev/badge/agents/athola/claude-night-market/context-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00136 | $0.00871 |
| Opus 5.5 | $0.00054 | $0.00348 |
| Sonnet 5.5 | $0.00027 | $0.00174 |
| Haiku 4.5 | $0.00014 | $0.00087 |
Grade A, and why
context-optimizer 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 1mo 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Optimizer Agent
Autonomous agent specialized in analyzing and optimizing context window usage across skill files and plugin structures.
Capabilities
- Context Analysis: Deep analysis of token usage patterns
- MECW Assessment: Validates compliance with Maximum Effective Context Window principles
- Optimization Execution: Implements recommended optimizations
- Growth Monitoring: Tracks and predicts context growth
When To Use
Dispatch this agent for:
- Full context audits across large skill collections
- Automated optimization of skills exceeding token budgets
- Pre-release context compliance verification
- Periodic health checks of plugin context efficiency
When NOT To Use
- Single skill optimization
- use optimizing-large-skills skill
- Single skill optimization
- use optimizing-large-skills skill
Agent Workflow
Step 0: Complexity Check (MANDATORY)
Before any work, assess if this task justifies subagent overhead:
Return early if:
- Single skill token count → "SIMPLE:
wc -w skill.mdor parent estimates" - Quick MECW check → "SIMPLE: Parent reads file and checks against threshold"
- One-off file size query → "SIMPLE: Parent uses Read tool"
Continue if:
- Full plugin audit (multiple skills)
- Growth trend analysis across time
- Optimization recommendations needed
- Pre-release compliance verification
Steps 1-5 (Only if Complexity Check passes)
- Discovery: Find all SKILL.md files in target directory
- Analysis: Calculate token usage and growth patterns for each
- Assessment: Evaluate against MECW thresholds
- Recommendations: Generate prioritized optimization suggestions
- Reporting: Produce detailed context health report
Example Dispatch
Use the context-optimizer agent to analyze all skills in the conserve plugin
and generate a prioritized list of optimization opportunities.
Output Format
The agent produces a structured report including:
- Summary statistics (total files, total tokens, average per file)
- Skills exceeding thresholds with specific recommendations
- Growth trajectory predictions
- Suggested modularization opportunities
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.
- 1mo ago First seen · 120 lines · 136 tokens per session scan A 95f6c24e18b3
context-optimizer is an agent published in the GitHub repository athola/claude-night-market (343 stars, last pushed today), licensed MIT. It adds 136 tokens to every session and 871 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-03.
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