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 skills add ulises-jeremias/agent-toolkit --skill workspacegit clone --depth 1 https://github.com/ulises-jeremias/agent-toolkitWrote 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/skills/ulises-jeremias/agent-toolkit/workspace)<a href="https://agentmods.dev/skills/ulises-jeremias/agent-toolkit/workspace"><img src="https://agentmods.dev/badge/skills/ulises-jeremias/agent-toolkit/workspace/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/skills/ulises-jeremias/agent-toolkit/workspace"><img src="https://agentmods.dev/badge/skills/ulises-jeremias/agent-toolkit/workspace.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00027 | $0.00948 |
| Opus 5.5 | $0.00011 | $0.00379 |
| Sonnet 5.5 | $0.00005 | $0.00190 |
| Haiku 4.5 | $0.00003 | $0.00095 |
Grade A, and why
workspace scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workspace
Initialize and operate the stateless AI workspace (~/.ai-workspace) that orchestrates work across any repo, team, or client via agent-toolkit workspace and agent-toolkit memory. This is the entry point for multi-repo delivery; all swarm and project work runs inside it.
When to use
- Starting a new session (
agent-toolkit workspace context+agent-toolkit memory inject+agent-toolkit memory todo— the session start protocol perAGENTS.md). - User needs to switch client/project context via packs (
packs/*.yaml). - Workspace health check, pack load, or knowledge sync is needed.
Prerequisites
agent-toolkitinstalled (agent-toolkit workspace --helpworks).- Workspace at
~/.ai-workspace(or$WORKSPACE_ROOT) withrepos/,projects/symlinks,knowledge/,personas/,packs/.
Workflow
1. Session start protocol (always)
agent-toolkit workspace context # inject session state (repos, packs, personas)
agent-toolkit memory inject # load persistent knowledge
agent-toolkit memory todo # show pending follow-ups
# Optional: load a pack
agent-toolkit workspace load packs/<client>.yaml
Per AGENTS.md: check knowledge/ before asking a question already answered; run discovery before large edits; follow plan → implement → review → PR.
2. Inspect and switch context
agent-toolkit workspace context --json | jq
ls ~/.ai-workspace/projects # symlinks to active repos
ls ~/.ai-workspace/packs
cat ~/.ai-workspace/AGENTS.md # portable contract (primary), plus CLAUDE.md/GEMINI.md symlinks
Packs bundle client/project context:
agent-toolkit workspace load packs/my-client.yaml # sets env, LLM policy, registry
# Verify LLM policy before queuing devcompanion jobs (esp. for client engagements)
dots-devcompanion llm-status # or agent-toolkit devcompanion status
3. Knowledge lifecycle
agent-toolkit memory search "topic" # find existing knowledge
agent-toolkit memory add --type learning "pattern" # save after discovering
agent-toolkit memory add --type todo "follow-up" # track
agent-toolkit memory todo # review before closing session
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.
- 1mo ago First seen · 104 lines · 27 tokens per session scan A e950294a680d
workspace is a skill published in the GitHub repository ulises-jeremias/agent-toolkit (19 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 948 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-04.
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