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 skills add bulbulogludemir/eachlabs-ai-plugin --skill eachlabsgit clone --depth 1 https://github.com/bulbulogludemir/eachlabs-ai-pluginWrote 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/skills/bulbulogludemir/eachlabs-ai-plugin/eachlabs)<a href="https://agentmods.dev/skills/bulbulogludemir/eachlabs-ai-plugin/eachlabs"><img src="https://agentmods.dev/badge/skills/bulbulogludemir/eachlabs-ai-plugin/eachlabs/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/skills/bulbulogludemir/eachlabs-ai-plugin/eachlabs"><img src="https://agentmods.dev/badge/skills/bulbulogludemir/eachlabs-ai-plugin/eachlabs.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 | $0.00077 | $0.01432 |
| Opus 5 | $0.00039 | $0.00716 |
| Sonnet 5 | $0.00015 | $0.00286 |
| Haiku 4.5 | $0.00008 | $0.00143 |
Grade A, and why
eachlabs 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 10d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
each::labs
Use this skill to build practical each::labs integrations in Codex. Prefer current official documentation over memory when endpoint details, model slugs, schemas, or pricing behavior matter.
Core Surfaces
- each::api: direct REST model execution at
https://api.eachlabs.ai. - each::workflows: multi-step pipelines at
https://workflows.eachlabs.run/api/v1. - each::sense: OpenAI-compatible generative media agent at
https://eachsense-agent.core.eachlabs.run. - LLM Router: OpenAI-compatible LLM access at
https://api.eachlabs.ai/v1. - MCP: bundled
eachlabsserver with docs proxy tools plus action tools.
Docs Workflow
When the bundled eachlabs MCP is available, use it for current docs lookup before implementing or answering precise API questions:
- Search with
search_each_labs. - Read exact pages with
query_docs_filesystem_each_labs. - Cite or link the public docs URL when reporting user-facing API facts.
If MCP tools are unavailable, use the public docs index at https://docs.eachlabs.ai/llms.txt.
Prefer its purpose-built tools over hand-written HTTP calls:
eachlabs_search_models,eachlabs_get_model, andeachlabs_get_model_request_schemafor model discovery and schemas.eachlabs_recommend_modelsfollowed byeachlabs_compare_modelsfor credit-free model selection using live schemas and catalog p50 latency.eachlabs_diff_model_schemabefore upgrades and deploys to detect breaking live-schema drift.eachlabs_create_prediction(modeasync,wait, orsync; validates input locally first) andeachlabs_get_prediction(wait=trueto poll) for direct generation; successful image outputs come back inline in chat.eachlabs_list_executionsfor raw run history,eachlabs_summarize_usagefor privacy-conscious cost/runtime summaries,eachlabs_diagnose_runfor local failure triage, andeachlabs_export_debug_bundlefor shareable diagnostics without sensitive payloads.eachlabs_upload_filefor local media inputs.eachlabs_audio_transcribeandeachlabs_audio_speechfor the dedicated audio APIs.eachlabs_create_workflow,eachlabs_execute_workflow, and workflow execution polling tools for workflows.eachlabs_validate_workflow_definitionbefore workflow mutation,eachlabs_diff_workflowbefore publishing a version, andeachlabs_generate_integration_codefor live-schema TypeScript, Python, Go, or cURL examples.eachsense_chat_completionandeachsense_build_workflowfor each::sense.eachlabs_llm_chat_completionfor LLM Router calls.
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.
- 10d ago First seen · 102 lines · 77 tokens per session scan A 846eba918de1
eachlabs is a skill published in the GitHub repository bulbulogludemir/eachlabs-ai-plugin (12 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 1,432 once invoked, about $0.0004 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 2026-08-30.
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