Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add matebenyovszky/agentplaybooks/plugin install agentplaybooksWrote 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/matebenyovszky/agentplaybooks/pull)<a href="https://agentmods.dev/commands/matebenyovszky/agentplaybooks/pull"><img src="https://agentmods.dev/badge/commands/matebenyovszky/agentplaybooks/pull/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/matebenyovszky/agentplaybooks/pull"><img src="https://agentmods.dev/badge/commands/matebenyovszky/agentplaybooks/pull.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 | $0.00015 | $0.00352 |
| Opus 5 | $0.00008 | $0.00176 |
| Sonnet 5 | $0.00003 | $0.00070 |
| Haiku 4.5 | $0.00002 | $0.00035 |
Grade A, and why
pull scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Pull a remote AgentPlaybooks playbook into the local project.
- If no playbook reference was given, run
node "${CLAUDE_PLUGIN_ROOT}/bin/agentplaybooks.js" playbooksand let the user pick one. If that fails with a missing-key error, ask the user to runagentplaybooks login(or setAGENTPLAYBOOKS_API_KEY) first — never ask them to paste the key into the chat. - Run:
node "${CLAUDE_PLUGIN_ROOT}/bin/agentplaybooks.js" pull $ARGUMENTS --json - Summarize the plan: whether the playbook's instructions would be written to
AGENTS.md, which skills would be created under.agents/skills/, which MCP servers would be added to.agents/mcp.json, and any conflicts with existing local files (these are skipped, never overwritten). OpenAPI federation servers are hosted-only and appear as conflicts by design. - Only after the user confirms, re-run with
--apply, then runsyncto propagate the pulled skills and MCP servers to the platform targets. On a fresh project no target exists yet, so readsuggestedTargetsfrom the sync plan and offersync --target=<types> --apply. - If the playbook declares
spec.secrets, list the environment variables the user still needs to set. Never ask for or echo their values.
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.
- 9d ago First seen · 25 lines · 15 tokens per session scan A a774eefa5a77
pull is a command published in the GitHub repository matebenyovszky/agentplaybooks (5 stars, last pushed 2d ago), licensed MIT. It adds 15 tokens to every session and 352 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 2026-08-31.
Other commands, from other repositories
CHANGELOG
Command "CHANGELOG" from bytedance/UI-TARS-desktop, covering 0.4.0 2024-12-10 - add logging, 1.2.29, 1.2.28, 1.2.26 and 1.2.25.
TODO
The Open-Source Multimodal AI Agent Stack: Connecting Cutting-Edge AI Models and Agent Infra.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.