agentmods.dev

LEAP

A skill-building workflow with one path for extracting a new skill from source material and another for combining an existing method with subject-specific skills.

In plain words
What is it for?
It helps run distillation or fusion pipelines, create research plans, resume later stages, merge findings, discover examples, and compile the final skill.
Why use it?
It provides a defined process for turning raw research or multiple skills into a reusable skill package.

Skill for Claude CodeCodex

342 8d ago A scan 52 tokens original MIT
View the source file agentsope/SkillAlchemy
Install

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.

agentmods
npx agentmods add skills/agentsope/skillalchemy/leap
Any agent
npx skills add agentsope/SkillAlchemy --skill leap
Clone the repo
git clone --depth 1 https://github.com/agentsope/SkillAlchemy

Made for: Claude Code, Codex.

Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,087 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00052 $0.07087
Opus 5 $0.00026 $0.03544
Sonnet 5 $0.00010 $0.01417
Haiku 4.5 $0.00005 $0.00709

Measured 2d ago against content hash 5edb267e29d5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

LEAP 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 2d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/build_component_index.py, scripts/build_corpus.py, scripts/download_subtitles.sh, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/LEAP/SKILL.md · 783 lines

How it starts

The opening of the file, as written. The whole thing — 783 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LEAP · Skill Builder

LEAP does not choose the request type or interact with the user. SkillAlchemy selects the branch and handles each user checkpoint. LEAP runs the selected pipeline and returns the result.

Branch Routing

Command Branch Pipeline
distill / distillation Branch A Distillation pipeline — extract the target OS from raw data and compile it into a persona/tool skill
fuse / fusion Branch B Fusion pipeline — method.skill (skeleton) × subject.skill(s) (flesh) → output.skill

Invocation Modes

Mode Trigger Behavior
Full run No special keyword Run the full pipeline and output a skill package
Plan only stop after Stage 3 or stop_after_stage: 3 Run Branch A Stages 1-3 only; stop after writing research_plan.json
Resume continue from Stage 4 or resume_from_stage: 4 Skip Branch A Stages 1-3; use the existing research_plan.json and run Stages 4-7 plus Gate 1

Branch A: Distillation Pipeline

Source Intake → Intake Assessment → Research Plan Design
  → Research Swarm → Gate 1: Merge
  → Exemplar Discovery → Synthesis (3 agents)
  → Skill Compilation

Core principle: extract the operating system behind the source, not just the content or answer.

A-Stage 1: Source Intake

Input: person, author, method, organization, domain, URL, repo, or local files.

Create package workspace at output/<target-slug>-skill/:

output/<target-slug>-skill/
├── README.md
├── SKILL.md.draft
├── references/             # agent reports + exemplars
├── intermediate/           # structured data
└── examples/               # persona: required; tool: optional

Do not pre-create templates/; output templates live in LEAP's shared layer and are not needed in the generated skill.

Write intermediate/open_world_task.json with the capability brief g, target, source-access specification S (allowed source types, retrieval channels, and exclusions), execution/package constraints C, and depth_level. Every later retrieval must comply with S; existing skills are not eligible exemplars unless S explicitly permits them.

Read the full file on GitHub · 783 lines

Files

What ships with it

19 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.

Changes

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.

  1. 2d ago First seen · 783 lines · 52 tokens per session scan A 5edb267e29d5

Subscribe to this mod's changes

LEAP is a skill published in the GitHub repository agentsope/SkillAlchemy (342 stars, last pushed 8d ago), licensed MIT. It adds 52 tokens to every session and 7,087 once invoked, about $0.0003 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.

Building agentsLearning and teachingagent-skillai-agentllm-agentskill-creationskill-engineeringskill-generation
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