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 amirkiarafiei/subagent-cli-skills --skill pi-cligit clone --depth 1 https://github.com/amirkiarafiei/subagent-cli-skillsWrote 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/amirkiarafiei/subagent-cli-skills/pi-cli)<a href="https://agentmods.dev/skills/amirkiarafiei/subagent-cli-skills/pi-cli"><img src="https://agentmods.dev/badge/skills/amirkiarafiei/subagent-cli-skills/pi-cli.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 5.1 | $0.00077 | $0.02426 |
| Opus 5 | $0.00039 | $0.01213 |
| Sonnet 5 | $0.00015 | $0.00485 |
| Haiku 4.5 | $0.00008 | $0.00243 |
Grade A, and why
pi-cli 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 today.
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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pi CLI (subagent/task delegation)
Documented, not verified. Written from Pi's published docs (pi.dev) on 2026-09-06 and not checked against an installed binary. Before trusting any flag here, run
pi --help; on a mismatch use what the binary actually offers and tell the user which line in this file is wrong.
Use Pi to run a separate long-horizon pass over the repo: multi-step implementation, broad refactors, batch file writes, or deep exploration—similar to handing a task to a subagent. You stay orchestrator: smaller prompts, less context burn.
When to use Pi
- Large or multi-step work: several files, phases, or checkpoints (feature slice, migration, test suite, docs sweep).
- Event-driven monitoring:
--mode jsonemits a JSON-lines event stream (agent_start,message_updatedeltas,tool_execution_*,agent_end) — ideal for watching a long delegation. - Multi-provider model choice:
--providerand--model <provider/id>with a--thinkinglevel. - Attachments: files are referenced with
@(pi -p @screenshot.png "What's in this image?"). - User explicitly asks for Pi or "use Pi for this."
When not to use
- Small / single-step tasks answerable with one or two edits or a short explanation.
- Tight feedback loops where the user wants rapid back-and-forth refinement in one thread.
- Untrusted or destructive work. Pi's docs state it "does not include a built-in sandbox" and that built-in tools "can read files, write files, edit files, and run shell commands with the permissions of the pi process." There is no tool-approval gate to fall back on — see below.
- Secrets or policy-sensitive flows—avoid piping credentials; redact before delegating.
- Low ROI (Return on Investment): if the task requires high precision over a single line, or composing the Handoff Table costs more than editing the file yourself.
Delegation and context (critical)
Isolated subagent context saves tokens but splits the story: Pi does not see the main session's full thread. Poor handoffs cause misread subtasks, conflicting assumptions (stack, style, APIs), and wasted edits.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today First seen · 160 lines · 77 tokens per session scan A 488ae489daac
pi-cli is a skill published in the GitHub repository amirkiarafiei/subagent-cli-skills (5 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 2,426 once invoked, about $0.0004 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 2026-09-08.
Other skills, from other repositories
rework-rate
Measure and interpret PR rework rate — the emerging 5th DORA metric.
review
Validate plans, execution, or PRs against wish criteria — returns SHIP / FIX-FIRST / BLOCKED with severity-tagged gaps.
work
Execute an approved wish plan — orchestrate subagents per task group with fix loops, validation, and review handoff.
project-context
Use PowerContext project memory and handoff tools through MCP when continuing prior work, recalling decisions, maintaining durable memory, or transferring work across tasks, sessions, or agents.
brainstorm
Explore ambiguous or early-stage ideas interactively — tracks wish-readiness and crystallizes into a design for wish.
wish
Convert an idea into a structured wish plan with scope, acceptance criteria, and execution groups for work.