Borrowing it
Nothing to install: this file belongs to disler/inkwell-agent-sandboxes-and-software-factory. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/disler/inkwell-agent-sandboxes-and-software-factory/main/.claude/commands/prime.mdgit clone --depth 1 https://github.com/disler/inkwell-agent-sandboxes-and-software-factoryWrote 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/disler/inkwell-agent-sandboxes-and-software-factory/prime)<a href="https://agentmods.dev/commands/disler/inkwell-agent-sandboxes-and-software-factory/prime"><img src="https://agentmods.dev/badge/commands/disler/inkwell-agent-sandboxes-and-software-factory/prime/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/commands/disler/inkwell-agent-sandboxes-and-software-factory/prime"><img src="https://agentmods.dev/badge/commands/disler/inkwell-agent-sandboxes-and-software-factory/prime.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 | $0.00033 | $0.01080 |
| Opus 5 | $0.00016 | $0.00540 |
| Sonnet 5 | $0.00007 | $0.00216 |
| Haiku 4.5 | $0.00003 | $0.00108 |
Grade A, and why
prime scanned grade A with 1 finding 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 13d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
6. Read `.claude/skills/sssf-sandbox-orchestrator/SKILL.md` and its `references/gotchas.md`. The governing rule is **thin skill, fat recipes**: every action should be a `just` command a human could type. Dropping to `ssh How it starts
The opening of the file, as written. The whole thing — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Orient yourself in a three-layer system: Inkwell (a small blog-writing app), the Super Simple Software Factory (deterministic Python owns the graph, coding agents are bounded phases inside it), and the sandbox mount system (six host-side phases that stand the whole thing up on a disposable exe.dev VM, run it, and watch it from outside). The app is the payload; the point is the loop that ships it without a human in the middle.
Workflow
-
Map the surface first, because it is the fastest way to see the shape:
just(four namespaces, nothing else), thenjust --list sbx,just --list adw,just --list obs,just --list local. The namespace answers where the work happens:sbxorchestrates VMs from the host,adwruns the workflows,localboots an orchestrator agent on this machine,obsreads the trace db. Thengit ls-files | head -60andls sandbox_mount/host sandbox_mount/guest just/sandbox. -
Read
TREE.md— every file that matters and why it exists, grouped by layer, ending with the five things that will bite you. It is the map; the rest of this workflow is the territory. ThenREADME.mdfor the three layers, thenspecs/sandbox-mount-system.html— the plan is the working checklist, with live checkboxes recording what has actually been verified on hardware versus what is still theory. Open it in a browser or read thedata-ck="... checked"attributes. Treat an unchecked box as "not proven", not "not written". -
Read
ai_docs/exedev_sandbox_mounting.md— every number in it was measured on live VMs, and several "obvious" designs were killed by those measurements (a custom Docker image buys ~1s;--setup-scriptcannot see--env; an unsyncedssh exe.dev cpsilently produced 5,641 zero-byte files). Do not re-derive these; do not contradict them without a new measurement. -
Read
justfileandjust/sandbox/mod.just. This is the load-bearing idea:just/sandbox/andsandbox_mount/host/are host-only — not because they are removed from the mounted copy (the whole repo ships intact) but because they need the exe.dev account andOPENROUTER_PROVISIONING_KEY, and neither credential ever leaves the host. A sandbox that runsjust sbx mountgets an auth failure, not a nested VM.
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.
- 13d ago First seen · 30 lines · 33 tokens per session scan A 669a3839ac05
prime is a command published in the GitHub repository disler/inkwell-agent-sandboxes-and-software-factory (154 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 1,080 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.