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 lebsral/DSPy-Programming-not-prompting-LMs-skills --skill dspy-bootstrap-finetunegit clone --depth 1 https://github.com/lebsral/DSPy-Programming-not-prompting-LMs-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/lebsral/dspy-programming-not-prompting-lms-skills/dspy-bootstrap-finetune)<a href="https://agentmods.dev/skills/lebsral/dspy-programming-not-prompting-lms-skills/dspy-bootstrap-finetune"><img src="https://agentmods.dev/badge/skills/lebsral/dspy-programming-not-prompting-lms-skills/dspy-bootstrap-finetune/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/lebsral/dspy-programming-not-prompting-lms-skills/dspy-bootstrap-finetune"><img src="https://agentmods.dev/badge/skills/lebsral/dspy-programming-not-prompting-lms-skills/dspy-bootstrap-finetune.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 | $0.00198 | $0.03958 |
| Opus 5 | $0.00099 | $0.01979 |
| Sonnet 5 | $0.00040 | $0.00792 |
| Haiku 4.5 | $0.00020 | $0.00396 |
Grade A, and why
dspy-bootstrap-finetune 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 12d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
4 files 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.
- 12d ago First seen · 303 lines · 198 tokens per session scan A 693ee40fe97a
dspy-bootstrap-finetune is a skill published in the GitHub repository lebsral/DSPy-Programming-not-prompting-LMs-skills (11 stars, last pushed 2mo ago), with no licence file. It adds 198 tokens to every session and 3,958 once invoked, about $0.0010 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.
Other skills, from other repositories
sgc-install-ai
A workflow for adding an AI feature to an existing or new app, from the user-facing entry point to the service that sends requests to AI models.
fec-drawio-studio
An editable workflow for making technical diagrams in draw.io (also called diagrams.net), with the original .drawio file saved alongside exported images or documents. It covers architecture, database, UML, sequence, flow, machine-learning, and code-structure diagrams.
app-icon-composer
Produce HIG-correct, Icon Composer-ready layered app icons for iOS/iPadOS/macOS/watchOS 26 (Liquid Glass) — apply Apple's app-icon guidelines, design the layer stack and Default/Dark/Mono appearances, and author the art as SVG the model can write directly (no paid generator required), falling back to image-gen MCPs…
apple-foundation-models
On-device AI with Apple's Foundation Models framework (import FoundationModels) in iOS 26 / Apple Intelligence — LanguageModelSession, guided generation with @Generable/@Guide, streaming, tool calling, and availability gating. Use when the user wants on-device LLM features, Apple Intelligence integration…
data-pipeline
Builds automated sports analytics pipelines -- daily data pulls, scheduled prediction generation, model versioning, prediction tracking, and drift alerting. Use when user asks how to automate their model, how to run predictions every morning, how to set up a cron job for sports data, how to track model performance…
model-building
Trains and validates prediction models for sports game outcomes. Use when user asks about building a prediction model, training a classifier, choosing between logistic regression or XGBoost, model selection, hyperparameter tuning, feature importance, or ensemble methods. Always uses walk-forward methodology -- refuses…