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 agentmods add commands/ashlrai/ashlr-plugin/ashlr-orchestrategit clone --depth 1 https://github.com/ashlrai/ashlr-pluginWrote 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/commands/ashlrai/ashlr-plugin/ashlr-orchestrate)<a href="https://agentmods.dev/commands/ashlrai/ashlr-plugin/ashlr-orchestrate"><img src="https://agentmods.dev/badge/commands/ashlrai/ashlr-plugin/ashlr-orchestrate.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00970 |
| Opus 5 | $0.00017 | $0.00485 |
| Sonnet 5 | $0.00007 | $0.00194 |
| Haiku 4.5 | $0.00003 | $0.00097 |
Grade A, and why
ashlr-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 4d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Description
Experimental MVP — stub executor by default. Each node currently runs a Bun subprocess that echoes
STUB-NODE: <id>rather than calling a real AI model. No actual work is performed on your codebase. SetASHLR_ORCHESTRATE_REAL_LLM=1to route nodes through the configured LLM provider (requiresANTHROPIC_API_KEYor a Pro token with cloud-LLM access). The real executor is read-only in this MVP — it produces a plan summary but does not write files or run commands.
/ashlr-orchestrate takes a free-text goal, auto-expands it into a small task graph (DAG of explore/implement/verify nodes scoped to a directory), shows you a dry-run preview, and on confirmation walks the graph in dependency order. Each node runs in its own sandbox so a failure in one branch doesn't poison the rest. This is the Q1 '27 distributed-orchestration MVP — local-only, capped at 3 nodes on Pro and 10 on Team. Free is blocked with a pointer to /ashlr-upgrade.
The flow is:
- Tier check (free → blocked, helpful upgrade message).
- Either auto-expand the goal into a graph or load a graph you wrote / edited as YAML (
--yaml <path>). - Render the DAG to stdout as a dry-run preview (goal, scope, tier, node count, per-node description + deps + scope + model).
- Prompt
y/n/e:yruns it.ncancels with exit 0.ewrites the current graph as YAML to~/.ashlr/orchestrate-edit-<id>.yaml, prints the path, and exits so you can hand-edit + re-run with--yaml.
- After the run, print a summary: total wall-clock, total tokens, per-node ok/fail.
--auto-confirm skips the prompt. --dry-run runs the graph in dry-run mode (no real subprocesses spawn).
Usage examples
# Goal-only — auto-expand against the current directory
/ashlr-orchestrate "refactor the auth flow to add MFA"
# Goal + explicit scope (limits the agents to one subtree)
/ashlr-orchestrate "harden retry logic" --scope ./servers
# Run a hand-edited or pre-saved YAML graph
/ashlr-orchestrate --yaml ./.ashlr/my-graph.yaml --auto-confirm
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.
- 4d ago First seen · 84 lines · 35 tokens per session scan A 5be09f5de329
ashlr-orchestrate is a command published in the GitHub repository ashlrai/ashlr-plugin (3 stars, last pushed 4d ago), licensed MIT. It adds 35 tokens to every session and 970 once invoked, about $0.0002 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 2026-08-31.
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