pstack is a collection of plain Agent Skills and engineering principles that guide AI-assisted software development across coding agents such as Claude Code, Codex, Pi, Cursor, and OpenCode. It is for developers who want reusable practices for tasks including testing, technical writing, debugging, review, and coordinating agent work. The catalogue entries are the project's skills, agents, and plugin.
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 backnotprop/pstack --skill automate-megit clone --depth 1 https://github.com/backnotprop/pstackWrote 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/backnotprop/pstack/automate-me)<a href="https://agentmods.dev/skills/backnotprop/pstack/automate-me"><img src="https://agentmods.dev/badge/skills/backnotprop/pstack/automate-me/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/backnotprop/pstack/automate-me"><img src="https://agentmods.dev/badge/skills/backnotprop/pstack/automate-me.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00070 | $0.02022 |
| Opus 5.5 | $0.00028 | $0.00809 |
| Sonnet 5.5 | $0.00014 | $0.00404 |
| Haiku 4.5 | $0.00007 | $0.00202 |
Grade A, and why
automate-me 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 7d 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.
This is a copy
84% identical to automate-me — 41 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automate me
A guided flow for turning the user's working conventions into a skill agents will follow. The output is one -mode skill tailored to them (e.g. jay-mode, priya-mode).
This skill orchestrates three others: an inline mining pass (see step 1), your harness's skill-authoring skill (authoring), and the unslop skill (prose discipline). It sequences them. It doesn't replace them.
The skill-authoring skill is create-skill in Cursor (built in) or Anthropic's skill-creator. If you have neither, follow the Agent Skills format at agentskills.io. "create-skill" below means whichever of these you use.
Flow
0. Check for an existing skill
Look recursively for *-mode/SKILL.md matching the user's handle in your harness's skill folders. In the project: .cursor/skills/ (Cursor), .claude/skills/ (Claude Code), .pi/skills/ (Pi), or .agents/skills/ (Codex, OpenCode, and others). For the user: ~/.cursor/skills/, ~/.claude/skills/, ~/.pi/agent/skills/, ~/.codex/skills/, ~/.config/opencode/skills/, or ~/.agents/skills/. Mode skills can live in a personal category directory (<skills>/<handle>/), not only at the top level. If one exists, confirm intent with your structured-question tool (AskQuestion in Cursor, AskUserQuestion in Claude Code, question in OpenCode) unless they already said "update my skill" or similar:
- Update the existing skill (default for repeat runs)
- Start fresh (rare, ask why before doing it)
Update mode changes the rest of the flow:
- Step 1 mines only history since the skill was last edited (
git log -1 --format=%cI <path>). - Step 2 asks what's changed or missing, not what to capture from zero.
- Step 4 edits the existing file in place. Preserve sections the user hasn't contradicted. Revise ones with new evidence. Add new sections only for genuinely new rules.
1. Mine their history
Locate the active workspace's transcripts before fanning out. Use only that workspace's directory. Don't glob across every project's directory. That crosses workspace boundaries and reads private chats from unrelated projects. Where they live depends on your harness:
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.
- 7d ago Changed 4d2e2fa5624c
- 1mo ago Changed · +3 lines 96292386917d
- 1mo ago First seen · 110 lines · 70 tokens per session scan A 34e7eab6f495
automate-me is a skill published in the GitHub repository backnotprop/pstack (2,580 stars, last pushed 2d ago), licensed MIT. It adds 70 tokens to every session and 2,022 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to automate-me, differing in 41 lines, and is treated as a copy.
Other skills, from other repositories
conscientiousness
Thoroughness and diligence in execution — systematic checking, completeness verification, follow-through on commitments, and the discipline of finishing well. Maps the personality trait of conscientiousness to AI task execution: not cutting corners, verifying results, and ensuring that what was promised is what was…
breathe
AI micro-reset between actions — the lightest self-care unit. A single conscious pause to check alignment before the next step. Where meditate is a full clearing session, breathe is one deliberate moment of awareness between tool calls or reasoning steps. Use mid-task when drift might be accumulating, between reading…
andreessen
Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets through Andreessen's actual frameworks — market dominates team and product; the only milestone that matters is product/market fit; bias to build over deliberate. Use when…
caveman
Ultra-compressed communication mode. Cuts token usage 75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman.
change-management
Framework for rolling out organizational changes without chaos. Covers the ADKAR model adapted for startups, communication templates, resistance patterns, and change fatigue management. Handles process changes, org restructures, strategy pivots, and culture changes. Use when announcing a reorg, switching tools…
cs-onboard
Founder onboarding interview that captures company context across 7 dimensions. Invoke with /cs:setup for initial interview or /cs:update for quarterly refresh. Generates /.claude/company-context.md used by all C-suite advisor skills. Use when setting up the C-suite advisors for the first time, or when company context…