Agent skill

Dspy Production Deployment

A skill your agent uses for deploying DSPy with save/load, configurecache, restrictpickle, trackusage, async execution, streaming, and production runtime controls.

MITAuto-check passedDevOps & Cloud

Install Dspy Production Deployment

skills CLI

$ npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install OmidZamani/dspy-skills dspy-production-deployment --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/OmidZamani/dspy-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dspy-production-deployment .claude/skills/dspy-production-deployment && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "dspy-production-deployment" agent skill from https://github.com/OmidZamani/dspy-skills/tree/master/skills/dspy-production-deployment into .claude/skills/dspy-production-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dspy-production-deployment", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/OmidZamani/dspy-skills/tree/master/skills/dspy-production-deployment

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install OmidZamani/dspy-skills dspy-production-deployment --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OmidZamani/dspy-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/dspy-production-deployment .agents/skills/dspy-production-deployment && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "dspy-production-deployment" agent skill from https://github.com/OmidZamani/dspy-skills/tree/master/skills/dspy-production-deployment into .agents/skills/dspy-production-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dspy-production-deployment", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install OmidZamani/dspy-skills dspy-production-deployment --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OmidZamani/dspy-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/dspy-production-deployment .cursor/skills/dspy-production-deployment && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "dspy-production-deployment" agent skill from https://github.com/OmidZamani/dspy-skills/tree/master/skills/dspy-production-deployment into .cursor/skills/dspy-production-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dspy-production-deployment", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/OmidZamani/dspy-skills.git --path skills/dspy-production-deployment

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install OmidZamani/dspy-skills dspy-production-deployment --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OmidZamani/dspy-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/dspy-production-deployment .gemini/skills/dspy-production-deployment && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "dspy-production-deployment" agent skill from https://github.com/OmidZamani/dspy-skills/tree/master/skills/dspy-production-deployment into .gemini/skills/dspy-production-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dspy-production-deployment", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install OmidZamani/dspy-skills dspy-production-deployment

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/OmidZamani/dspy-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/dspy-production-deployment .github/skills/dspy-production-deployment && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "dspy-production-deployment" agent skill from https://github.com/OmidZamani/dspy-skills/tree/master/skills/dspy-production-deployment into .github/skills/dspy-production-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dspy-production-deployment", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install OmidZamani/dspy-skills dspy-production-deployment --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OmidZamani/dspy-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/dspy-production-deployment .opencode/skills/dspy-production-deployment && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "dspy-production-deployment" agent skill from https://github.com/OmidZamani/dspy-skills/tree/master/skills/dspy-production-deployment into .opencode/skills/dspy-production-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dspy-production-deployment", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: dspy-production-deployment
GitHub stars: 123
Token cost: ~839 tokens
SKILL.md length: 211 words
Files: 2
Skills in repo: 17
Repo updated: Jun 23, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

A skill your agent uses for deploying DSPy with save/load, configurecache, restrictpickle, trackusage, async execution, streaming, and production runtime controls.

Works in 6 steps: Pin the stable DSPy series. → Use state-only JSON unless whole-program… → Enable restrict_pickle=True. → …
Deploying DSPy with save/load
SKILL.md covers Goal, Cache Hardening, Save and Load and Usage Tracking, plus 4 more sections
Runs Python scripts from its folder

What it does

Dspy Production Deployment is an agent skill from OmidZamani/dspy-skills. Use for deploying DSPy with save/load, configurecache, restrictpickle, trackusage, async execution, streaming, and production runtime controls.

Its SKILL.md is about 840 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `example.py`).

It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: Collection of Claude Skills for DSPy framework - program language models, optimize prompts, and build RAG pipelines systematically. The licence is MIT.

When your agent uses it

Deploying DSPy with save/load
Async execution
Production runtime controls

Example prompts

“/dspy-production-deployment”

Requirements

Python 3
Pre-approved tools (allowed-tools): Read, Write, Glob, Grep

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

Pin the stable DSPy series.
Use state-only JSON unless whole-program pickle is necessary and trusted.
Enable restrict_pickle=True.
Record usage, latency, errors, and traces.
Load-test async and streaming paths separately.
Use dspy-debugging-observability for MLflow and callbacks.

What it can do on your machine

Read from SKILL.md and the folder at commit f5db3b7. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Read
- Write
- Glob
- Grep
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- dspy.ai
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Dspy Production Deployment loads about 839 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 211 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~43
When it runs · the whole SKILL.md, loaded when a task matches: ~839

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from OmidZamani/dspy-skills at commit f5db3b7, republished under its MIT licence (© OmidZamani). 211 words, ~839 tokens.

Download SKILL.mdSave it as .claude/skills/dspy-production-deployment/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: dspy-production-deployment
description: Use for deploying DSPy with save/load, configure_cache, restrict_pickle, track_usage, async execution, streaming, and production runtime controls.
allowed-tools: Read, Write, Glob, Grep
version: 1.0.0
dspy-compatibility: 3.2.1
tags: production

DSPy Production Deployment

Goal

Prepare a DSPy program for repeatable, observable, scalable, and safer production execution.

Cache Hardening

DSPy enables memory and disk caches by default. Disk cache deserialization uses pickle unless restricted. Enable the allowlist mode in production:

python

import dspy

dspy.configure_cache(restrict_pickle=True)

python

dspy.configure_cache(
    restrict_pickle=True,
    safe_types=[MyResult, Metadata],
)

Disable a cache layer explicitly when a deployment cannot persist data or requires fresh model responses:

python

dspy.configure_cache(
    enable_disk_cache=False,
    enable_memory_cache=True,
)

Save and Load

Prefer state-only JSON for readable, safer artifacts:

python

compiled.save("./artifacts/program.json", save_program=False)

loaded = MyProgram()
loaded.load("./artifacts/program.json")

Use whole-program save only for trusted artifacts. It uses cloudpickle:

python

compiled.save("./artifacts/program/", save_program=True)
loaded = dspy.load("./artifacts/program/")

Keep the DSPy major version compatible when loading saved programs.

Usage Tracking

python

dspy.configure(
    lm=dspy.LM("openai/gpt-4o-mini"),
    track_usage=True,
)

prediction = program(question="What is DSPy?")
print(prediction.get_lm_usage())

Cached calls return no new token usage.

Async Execution

Most built-in modules support acall():

python

import asyncio

async def main():
    prediction = await program.acall(question="What is DSPy?")
    print(prediction.answer)

asyncio.run(main())

Implement aforward() for custom async modules. Use dspy.asyncify(program) only when adapting a synchronous callable is the right boundary.

Streaming

python

import asyncio
import dspy

stream_program = dspy.streamify(
    dspy.Predict("question -> answer"),
    stream_listeners=[
        dspy.streaming.StreamListener(signature_field_name="answer"),
    ],
)

async def main():
    async for chunk in stream_program(question="Explain DSPy briefly."):
        print(chunk)

asyncio.run(main())

For looped modules such as ReAct, set allow_reuse=True on listeners for repeated fields. Cache hits yield the final Prediction without replaying token chunks.

Production Checklist

Pin the stable DSPy series.
Use state-only JSON unless whole-program pickle is necessary and trusted.
Enable restrict_pickle=True.
Record usage, latency, errors, and traces.
Load-test async and streaming paths separately.
Use dspy-debugging-observability for MLflow and callbacks.

Official Documentation

Production guide: https://dspy.ai/production/
Cache tutorial: https://dspy.ai/tutorials/cache/
Saving tutorial: https://dspy.ai/tutorials/saving/
Async tutorial: https://dspy.ai/tutorials/async/
Streaming tutorial: https://dspy.ai/tutorials/streaming/

Files

SKILL.md and 1 other file in skills/dspy-production-deployment of OmidZamani/dspy-skills.

SKILL.md
example.py

Open the folder on GitHubat commit f5db3b7

Compare with similar skills

Dspy Production Deployment next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Dspy Production Deployment compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Dspy Production Deployment this skillOmidZamani/dspy-skills	123	—	~839	Automated safety check: Pass	MIT	3 mo ago
Kubeshark Installerkubeshark/kubeshark	12k	—	~3.6k	Automated safety check: Notes	Apache-2.0	yesterday
GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb	6.7k	—	~4k	Automated safety check: Notes	Apache-2.0	yesterday
Mirrord Operatormetalbear-co/mirrord	5.4k	1 repos	~4.6k	Automated safety check: Pass	MIT	today
KubeSphere ServiceMesh Managerkubesphere/kubesphere	17k	—	~2.4k	Automated safety check: Pass	Custom licence	2 mo ago
Vercelremotion-dev/remotion	63k	—	~1.2k	Automated safety check: Pass	Custom licence	2 days ago

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Questions about Dspy Production Deployment

What does Dspy Production Deployment do?

A skill your agent uses for deploying DSPy with save/load, configurecache, restrictpickle, trackusage, async execution, streaming, and production runtime controls. Dspy Production Deployment is an agent skill from OmidZamani/dspy-skills. Use for deploying DSPy with save/load, configurecache, restrictpickle, trackusage, async execution, streaming, and production runtime controls.

When should I use Dspy Production Deployment?

Dspy Production Deployment fits situations like: deploying DSPy with save/load; async execution; production runtime controls.

How do I install Dspy Production Deployment in Claude Code?

Run `npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a claude-code`. Or copy the skill folder (skills/dspy-production-deployment in OmidZamani/dspy-skills) into .claude/skills/dspy-production-deployment in your project. Claude Code loads it when a task matches its description.

How do I install Dspy Production Deployment in Codex?

Run `npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a codex`. Or copy the skill folder (skills/dspy-production-deployment in OmidZamani/dspy-skills) into .agents/skills/dspy-production-deployment in your project. Codex loads it when a task matches its description.

Can I use Dspy Production Deployment in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OmidZamani/dspy-skills --skill dspy-production-deployment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dspy-production-deployment, .gemini/skills/dspy-production-deployment, .github/skills/dspy-production-deployment and .opencode/skills/dspy-production-deployment in your project.

What does Dspy Production Deployment need to run?

Going by SKILL.md and its folder, Dspy Production Deployment needs Python for the scripts in its folder. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Glob, Grep.

Does Dspy Production Deployment access the network?

SKILL.md names 1 domain. As links in the text: dspy.ai. This is read from the text; nothing was executed.

Is Dspy Production Deployment safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Dspy Production Deployment use?

Dspy Production Deployment is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Dspy Production Deployment use?

About 839 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Dspy Production Deployment?

Skills that share tags, products or a category with Dspy Production Deployment: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), Mirrord Operator (metalbear-co/mirrord, 5.4k stars) and KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dspy Production Deployment?

OmidZamani (a GitHub user) maintains it in OmidZamani/dspy-skills, which has 123 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on June 23, 2026.

Source: OmidZamani/dspy-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Dspy Production Deployment

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

DSPy Production Deployment

Goal

Cache Hardening

Save and Load

Usage Tracking

Async Execution

Streaming

Production Checklist

Official Documentation

Files

Compare with similar skills

Similar skills

More from OmidZamani/dspy-skills

Related

Questions about Dspy Production Deployment