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 ayushcodes10/echo-mem --skill stream-chaingit clone --depth 1 https://github.com/ayushcodes10/echo-memWrote 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/ayushcodes10/echo-mem/stream-chain)<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/stream-chain"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/stream-chain/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/ayushcodes10/echo-mem/stream-chain"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/stream-chain.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 | $0.00018 | $0.02759 |
| Opus 5.5 | $0.00007 | $0.01104 |
| Sonnet 5.5 | $0.00004 | $0.00552 |
| Haiku 4.5 | $0.00002 | $0.00276 |
Grade A, and why
stream-chain 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.
This is a copy
97% identical to stream-chain — 83 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 561 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stream-Chain Skill
Execute sophisticated multi-step workflows where each agent's output flows into the next, enabling complex data transformations and sequential processing pipelines.
Overview
Stream-Chain provides two powerful modes for orchestrating multi-agent workflows:
- Custom Chains (
run): Execute custom prompt sequences with full control - Predefined Pipelines (
pipeline): Use battle-tested workflows for common tasks
Each step in a chain receives the complete output from the previous step, enabling sophisticated multi-agent coordination through streaming data flow.
Quick Start
Run a Custom Chain
Codex-flow stream-chain run \
"Analyze codebase structure" \
"Identify improvement areas" \
"Generate action plan"
Execute a Pipeline
Codex-flow stream-chain pipeline analysis
Custom Chains (run)
Execute custom stream chains with your own prompts for maximum flexibility.
Syntax
Codex-flow stream-chain run <prompt1> <prompt2> [...] [options]
Requirements:
- Minimum 2 prompts required
- Each prompt becomes a step in the chain
- Output flows sequentially through all steps
Options
| Option | Description | Default |
|---|---|---|
--verbose |
Show detailed execution information | false |
--timeout <seconds> |
Timeout per step | 30 |
--debug |
Enable debug mode with full logging | false |
How Context Flows
Each step receives the previous output as context:
Step 1: "Write a sorting function"
Output: [function implementation]
Step 2 receives:
"Previous step output:
[function implementation]
Next task: Add comprehensive tests"
Step 3 receives:
"Previous steps output:
[function + tests]
Next task: Optimize performance"
Examples
Basic Development Chain
Codex-flow stream-chain run \
"Write a user authentication function" \
"Add input validation and error handling" \
"Create unit tests with edge cases"
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 Changed cdafdb2b67ce
- 1mo ago First seen · 561 lines · 18 tokens per session scan A 09a978590c2c
stream-chain is a skill published in the GitHub repository ayushcodes10/echo-mem (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 2,759 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to stream-chain, differing in 83 lines, and is treated as a copy.
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