smithery.ai

chain-load

Load a chain to restore context from previous work. Use anytime when working on related topics - proactively search and suggest relevant chains.

First seen May 2, 2026

Installation

$ npx skills add https://smithery.ai

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from smithery.ai · top by installs.

npx skills add https://smithery.ai

Browse all from smithery.ai

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,867 B
  • docs SUMMARY.md 162 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Chain Load - Load Work Context

Load chain links to restore context. Can be used anytime, not just at session start.

Usage

/chain-load [chain-name]
/chain-load [search-query]

Proactive Behavior

When working on a task, proactively check for relevant context:

  1. Use tinymemchainsearch to find chains matching current work topic
  2. Use tinymem_search to find individual memory segments
  3. Suggest loading relevant chains or segments to the user

Segments vs Chains:

  • Segments (memories): Individual insights via tinymemsearch + tinymemget
  • Chains: Full workflow context via tinymemchainload

Instructions

  1. Find Chain:

- If exact chain-name provided → use tinymemchainload - If query provided → use tinymemchainsearch for fuzzy matching - If nothing provided → use tinymemchainlist to show all

  1. Load Chain Links - Call tinymemchainload:

- chain_name: the chain to load - limit: 5 (default, most recent links)

  1. Parse and Present Context - Extract from XML:

- Previous summaries - Decisions with rationale - Code changes history - Outstanding issues - Next steps

Output Format

## Chain: [name] ([count] links)

### Latest: [slug] - [date]
<summary and next-steps from most recent link>

### Context
<key decisions and history from older links>

### Suggested Action
[Next step based on chain state]

Examples

User: /chain-load auth-feature → Loads auth-feature chain

User: /chain-load auth → Searches chains matching "auth"

User working on auth code (proactive): → Agent: "Found chain 'auth-feature' with 3 links. Load context?"