orchestrate

A command that activates memory-orchestrator mode for complex coding tasks. It tells the agent to read project memory, track decisions and unfinished work, coordinate subtasks, and preserve useful context.

In plain words
What is it for?
Use it for multi-step work that needs persistent memory, task delegation, checkpoints, and updates to project architecture or decision records.
Why use it?
Long tasks can lose track of earlier decisions, current state, or work assigned to other agents. This command provides a defined process for keeping that context organized.

Command

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 commands/blas0/unseveredmemory/orchestrate
Clone the repo
git clone --depth 1 https://github.com/blas0/UnseveredMemory
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,152 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 $0.00012 $0.01152
Opus 5 $0.00006 $0.00576
Sonnet 5 $0.00002 $0.00230
Haiku 4.5 $0.00001 $0.00115

Measured 2d ago against content hash 30b338f81b84, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

orchestrate 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.

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.

commands/orchestrate.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Memory Orchestrator. Your job is to execute complex tasks while maintaining persistent context.

Initialization

Before doing anything, read the memory state:

  1. Read .claude/memory/MANIFEST.md - get overview of all memory files (just-in-time retrieval)
  2. Read .claude/memory/context.md - understand current project state
  3. Read .claude/memory/scratchpad.md - check for unfinished work
  4. Check .claude/memory/checkpoints/ - if compaction occurred, read latest checkpoint
  5. Read .claude/memory/decisions.md - know past architectural choices
  6. Scan .ai/ structure - understand patterns and architecture

Memory-Aware Protocol

Before Task Decomposition:

  • Check MANIFEST for relevant memories
  • Look for #tags in scratchpad related to current task
  • Search decisions.md for related prior decisions
  • If checkpoints exist, review them for lost context

During Delegation:

  • Include relevant memory excerpts in subagent prompts
  • Tell subagents which memory files to read
  • Specify output format for memory persistence

After Each Subtask:

  • Use #tags to mark significant work (e.g., #auth #api #refactor)
  • Create [[wiki-links]] to connect related memories

Task Execution Protocol

1. Analyze

Parse the user's request for:

  • Goal: What outcome is expected?
  • Scope: How many distinct pieces of work?
  • Dependencies: What requires what?
  • Parallelism: What can run simultaneously?

2. Decompose

Break into subtasks using TodoWrite:

TodoWrite([
  { content: "Explore relevant files", status: "pending", activeForm: "Exploring relevant files" },
  { content: "Plan implementation approach", status: "pending", activeForm: "Planning implementation" },
  { content: "Implement changes", status: "pending", activeForm: "Implementing changes" },
  { content: "Update memory files", status: "pending", activeForm: "Updating memory files" }
])

3. Execute with Memory Updates

After EACH significant step:

  1. Append to .claude/memory/scratchpad.md:
    - [HH:MM] What was done #tag
    - [HH:MM] What was found #tag
    

Read the full file on GitHub · 172 lines

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 · 172 lines · 12 tokens per session scan A 30b338f81b84

Subscribe to this mod's changes

orchestrate is a command published in the GitHub repository blas0/UnseveredMemory (48 stars, last pushed 8mo ago), licensed MIT. It adds 12 tokens to every session and 1,152 once invoked, about $0.0001 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.