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Documentation Index

Fetch the complete documentation index at: https://www.edgee.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

Codex compression Codex Compression is the Edgee compression bundle tuned for Codex traffic — the three named strategies described in Token Compression, pre-configured for the OpenAI Responses wire format that Codex uses. You choose which strategies to enable. The CLI turns on a sensible default; the Console lets you toggle each one per API key.
StrategyWhat it does for CodexDefaultCustomer-traffic average
Tool ResultTrims tool-call outputs (file reads, shell commands, search results) before they reach the model. Lossless.✅ on−19%
Tool Surface (alpha)Drops MCP servers, skills, and tools irrelevant to the current task before the request hits the model.⚠️ opt-in~−25% projected
OutputReduces verbosity of model responses without losing technical content. Same answer, fewer tokens.⚪ opt-in−6.5% when enabled
Per-strategy averages don’t aggregate — they’re measured on different baselines. Customer aggregate token-bill reduction across active customers (rolling 30 days) sits at approximately 20%, with zero measurable drift on SWE-Bench Verified samples.

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Tool Result Trimming

tool_result_trimming filters the tool-call outputs Codex receives — file reads, shell commands, search results — before they reach the model. Lossless on tool-result payloads. User messages and assistant turns are not modified. → Full strategy reference: Token Compression / Tool Result Trimming.

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Tool Surface Reduction (alpha)

tool_surface_reduction strips out the MCP servers, skills, and tools Codex wouldn’t use for the current task. The IDE still exposes everything; the model only ever sees the relevant subset. → Full strategy reference: Token Compression / Tool Surface Reduction.

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Output Brevity (by Caveman)

output_brevity reduces the verbosity of Codex’s responses. Three strategies are available (light, medium, hard). Off by default for Codex sessions because output is a small share (~1%) of total volume — turn it on if your Codex workflow leans heavy on long-form responses. → Full strategy reference: Token Compression / Output Brevity.

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Receipts

−49.5% fresh input tokens (1.14M → 574K per session). −35.6% total session cost (4.00→4.00 → 2.58). Cache hit rate 76% → 85%. Source: edgee-ai/compression-lab · Stop paying Codex to re-read context

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Get started

edgee launch codex
If the Edgee CLI isn’t installed yet: 
curl -fsSL https://install.edgee.ai | bash
After your session, the CLI prints a link to view per-strategy savings in the Edgee Console.

CLI guide

Install, authenticate, and launch Codex in under a minute.

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Codex-specific: OpenAI Responses wire format

Codex uses the OpenAI responses wire API. When routing through Edgee, the CLI automatically sets the correct provider config in ~/.codex/config.toml: 
model_provider = "edgee"

[model_providers.edgee]
name = "EDGEE"
base_url = "https://api.edgee.ai/v1"
http_headers = { "x-edgee-api-key" = "<YOUR_EDGEE_API_KEY>" }
wire_api = "responses"
This is handled automatically by edgee launch codex. You never need to edit this file manually.

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Toggling individual strategies

In the Edgee Console, open Dashboard and manage your Codex’s settings right from the UI.
  • Enable tool_surface_reduction to opt into the alpha tool-surface compression.
  • Enable output_brevity if your Codex workflow produces long-form output worth tightening.
  • Disable tool_result_trimming only when you want to compare against an uncompressed baseline.
For team-managed keys, the same toggles are available per-member from Team management → agent settings. See Team management.
To configure Codex without the CLI, paste the config above into ~/.codex/config.toml and replace <YOUR_EDGEE_API_KEY> with your key from the Edgee Console. Then enable the strategies you want from the Edge Models section.

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Lossiness

tool_result_trimming is lossless on tool-result payloads. tool_surface_reduction is lossless on the model’s perspective of available tools. output_brevity is not lossless on the prose dimension — it intentionally compresses prose verbosity. Across active customers (rolling 30 days), aggregate token bills are reduced by approximately 20% with zero measurable drift on SWE-Bench Verified samples.

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Next

Token Compression

Deep dive on each strategy.
https://mintcdn.com/edgee/RmPUqoqJw-u0FxFP/images/icons/claude.svg?fit=max&auto=format&n=RmPUqoqJw-u0FxFP&q=85&s=d3154991b618d253ee22ffaf55a433fc

Claude Code Compression

Same three strategies, tuned for Claude Code.