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 OmidZamani/dspy-skills --skill dspy-adapters-multimodalgit clone --depth 1 https://github.com/OmidZamani/dspy-skillsWrote 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/omidzamani/dspy-skills/dspy-adapters-multimodal)<a href="https://agentmods.dev/skills/omidzamani/dspy-skills/dspy-adapters-multimodal"><img src="https://agentmods.dev/badge/skills/omidzamani/dspy-skills/dspy-adapters-multimodal/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/omidzamani/dspy-skills/dspy-adapters-multimodal"><img src="https://agentmods.dev/badge/skills/omidzamani/dspy-skills/dspy-adapters-multimodal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.00841 |
| Opus 5.5 | $0.00018 | $0.00336 |
| Sonnet 5.5 | $0.00009 | $0.00168 |
| Haiku 4.5 | $0.00005 | $0.00084 |
Grade A, and why
dspy-adapters-multimodal 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DSPy Adapters and Multimodal I/O
Goal
Choose an adapter deliberately and model image, audio, and file inputs with DSPy's typed primitives.
Adapter Selection
| Adapter | Use it for |
|---|---|
dspy.ChatAdapter() |
Default, human-readable field markers, broad model compatibility |
dspy.JSONAdapter() |
Structured JSON output and native function calling where supported |
dspy.XMLAdapter() |
XML-tagged fields when XML is easier for the target LM to follow |
dspy.TwoStepAdapter() |
A separate extraction pass when parsing needs extra help |
Configure globally or for a limited scope:
import dspy
dspy.configure(
lm=dspy.LM("openai/gpt-4o-mini"),
adapter=dspy.JSONAdapter(),
)
with dspy.context(adapter=dspy.XMLAdapter()):
result = dspy.Predict("question -> answer")(question="What is DSPy?")
Native Function Calling
JSONAdapter enables native function calling by default. ChatAdapter keeps text parsing by default. Override either behavior explicitly:
chat_native = dspy.ChatAdapter(use_native_function_calling=True)
json_manual = dspy.JSONAdapter(use_native_function_calling=False)
DSPy falls back to manual parsing when the configured LM does not support native function calling.
Image Inputs
class DescribeImage(dspy.Signature):
image: dspy.Image = dspy.InputField()
description: str = dspy.OutputField()
describe = dspy.Predict(DescribeImage)
result = describe(image=dspy.Image("./diagram.png"))
Pass a local path, HTTP URL, bytes, PIL image, or existing data URI directly to dspy.Image(...).
Audio and File Inputs
class SummarizeAudio(dspy.Signature):
audio: dspy.Audio = dspy.InputField()
summary: str = dspy.OutputField()
audio = dspy.Audio.from_file("./meeting.wav")
summary = dspy.Predict(SummarizeAudio)(audio=audio)
class SummarizeFile(dspy.Signature):
file: dspy.File = dspy.InputField()
summary: str = dspy.OutputField()
document = dspy.File.from_path("./research.pdf")
summary = dspy.Predict(SummarizeFile)(file=document)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 110 lines · 45 tokens per session scan A 55dc22b27c65
dspy-adapters-multimodal is a skill published in the GitHub repository OmidZamani/dspy-skills (124 stars, last pushed 4mo ago), licensed MIT. It adds 45 tokens to every session and 841 once invoked, about $0.0002 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 2026-08-30.
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