Agent skill

Setup P3

by uzairansaruzi in uzairansaruzi/p3-stack

Configure which models p3-stack uses per role and at what reasoning budget.

MITAuto-check passed

Install Setup P3

skills CLI
$ npx skills add uzairansaruzi/p3-stack --skill setup-p3 -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install uzairansaruzi/p3-stack setup-p3 --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/uzairansaruzi/p3-stack.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/setup-p3 .claude/skills/setup-p3 && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
setup-p3
GitHub stars
143
Token cost
~1.5k tokens
SKILL.md length
689 words
Files
1
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

Configure which models p3-stack uses per role and at what reasoning budget.

  • Works in 7 steps: Detect available models → Load current state → Budget, map, and confirm → …
  • Configure p3 models
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Changing p3-stacks model choices

What it does

Setup P3 is an agent skill from uzairansaruzi/p3-stack. Configure which models p3-stack uses per role and at what reasoning budget. Detects your available models and writes p3-models.md, which overrides the skill defaults. Use for /setup-p3, "configure p3 models", "p3 budget", or changing p3-stack's model choices.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: pstack reworked for T3 Code: delegated subagents, worktree threads, PR watching, scheduled runs. The licence is MIT.

When your agent uses it

  • Configure p3 models
  • Changing p3-stacks model choices

Example prompts

  • “configure p3 models”
  • “p3 budget”
  • “/setup-p3”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Detect available models
  2. Load current state
  3. Budget, map, and confirm
  4. Validate
  5. Write the file
  6. Confirm
  7. Offer a verification skill (optional)

What it can do on your machine

Read from SKILL.md and the folder at commit 09909eb. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Setup P3 loads about 1.5k tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 689 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from uzairansaruzi/p3-stack at commit 09909eb, republished under its MIT licence (© uzairansaruzi). 689 words, ~1,471 tokens.

Download SKILL.mdSave it as .claude/skills/setup-p3/SKILL.md (or your agent's skills folder).
name
setup-p3
description
Configure which models p3-stack uses per role and at what reasoning budget. Detects your available models and writes p3-models.md, which overrides the skill defaults. Use for /setup-p3, "configure p3 models", "p3 budget", or changing p3-stack's model choices.
disable-model-invocation
true

Setup p3

Write p3-models.md, a file that sets p3-stack's model per role. Default location is the current project root. Offer ~/.agents/p3-models.md as the global option, and ask which one. A project file wins over the global one.

Steps

1. Detect available models

Call orchestrator_capabilities. It lists the providers and models you can pass to delegate_task in this session, custom models included, with each one's provider instance ID and any reasoning options. That is the only source. If it returns nothing, stop and tell the user. Never write a provider or model it did not return. inherit-parent is always valid even though it is not a detected model.

2. Load current state

The roles are the labels shown in step 5. If p3-models.md already exists at the chosen location, read it and treat its # budget line and its role values as the current choices. Otherwise start from the defaults in step 3(b). A line whose role is not in step 5, such as how critics, is from a retired role. Drop it.

3. Budget, map, and confirm

(a) Ask for a budget. Ask plainly in the thread. Offer these four options with these exact labels, and name the current budget when the file records one.

  • unlimited — keep max
  • large — xhigh reasoning
  • medium — high reasoning
  • small — medium reasoning

(b) Apply it. Build the working table. On a fresh run, give code roles (feature, refactoring, bug-fix, perf-issue, hillclimb) and the explorer, investigator, and swarm roles the fastest strong coding model detected. Give judgment and prose, hardest tasks, the explainer, the synthesizers, and reflect tooling the most capable model detected. Fill each panel role with one entry per distinct provider detected, up to three. On a re-run, keep any role the user changed.

When the catalog exposes reasoning options for a model, set each real entry's effort option from the budget: unlimited takes the highest option, and large, medium, and small take xhigh, high, or medium. The ladder is max > xhigh > high > medium > low. If the model does not expose the target, use the highest option at or below it, else mark the role as needing a choice. inherit-parent does not change. When the catalog exposes no reasoning options, map roles only and drop effort tokens; the budget label is still recorded.

(c) Show the roles and confirm. Show every role with its model, marking any entry not in the detected set as needing a choice. Also list each line step 2 dropped. Ask whether to accept as-is or change specific roles, offering the detected models plus inherit-parent (the role runs on the parent thread's model, so omit the model in delegate_task) as the options. For panel roles (arena runners, architect runners, interrogate reviewers) the value is a list, and one delegate_task runs per entry, inherit-parent entries included, so the list length sets the count. arena cross-judge pool is also a list, but Arena selects one value from it whose provider differs from the parent's when possible. swarm workers is the default model for every worker unless a race or comparison assigns another model per arm.

Show full SKILL.md (177 more words)Show less
4. Validate

Every real entry written must be in the orchestrator_capabilities result, under the provider instance it came from. inherit-parent always passes. If a chosen entry is not available, stop and ask again.

5. Write the file

Write p3-models.md with a # budget line with the chosen label and its target effort, and one line per role, using the same labels p3-mode uses. Write each entry as <providerInstanceId>/<model>, followed by its effort option in parentheses when step 3(b) set one. Overwrite the whole file so re-runs stay idempotent. Shape:

# p3 model configuration. One line per role. Delete a line to fall back to the skill default.
# `inherit-parent` as a value: the role runs on the parent thread's model (omit the delegate_task model). Entries in a panel list still count toward its fan-out.
# budget: unlimited (max)
feature, refactoring: <providerInstanceId>/<model> (<effort>)
bug-fix: <providerInstanceId>/<model> (<effort>)
perf-issue: <providerInstanceId>/<model> (<effort>)
hillclimb: <providerInstanceId>/<model> (<effort>)
judgment and prose: <providerInstanceId>/<model> (<effort>)
hardest tasks: <providerInstanceId>/<model> (<effort>)
how explorer: <providerInstanceId>/<model> (<effort>)
how explainer: <providerInstanceId>/<model> (<effort>)
why investigators: <providerInstanceId>/<model> (<effort>)
why synthesizer: <providerInstanceId>/<model> (<effort>)
reflect tooling: <providerInstanceId>/<model> (<effort>)
reflect judgment, divergent, synthesizer: <providerInstanceId>/<model> (<effort>)
arena runners: <entry>, <entry>, <entry>
arena cross-judge pool: <entry>, <entry>, <entry>
swarm workers: <providerInstanceId>/<model> (<effort>)
architect runners: <entry>, <entry>, <entry>
interrogate reviewers: <entry>, <entry>, <entry>
6. Confirm

Tell the user the file was written, where, and that it applies to new sessions. Re-running this skill updates it.

7. Offer a verification skill (optional)

Check whether the project has a way to drive the real app for proof (a verify-* skill, or an existing harness). If not, offer once: "want a project-local verification skill, so agents can drive the app the way a user does and prove changes work? I can generate one with /create-verification-skill." On yes, invoke /create-verification-skill. On no, move on without pushing.

© uzairansaruzi, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/setup-p3 of uzairansaruzi/p3-stack.

Open the folder on GitHubat commit 09909eb

Compare with similar skills

Setup P3 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Setup P3 compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Setup P3 this skilluzairansaruzi/p3-stack143—~1.5kAutomated safety check: PassMIT
Configure Channelopenclaw/openclaw392k—~946Automated safety check: PassMIT
ConfigurationBuilderIO/agent-native7.1k—~2.1kAutomated safety check: PassNone
Aria Rolesthedaviddias/Front-End-Checklist74k—~515Automated safety check: PassMIT
Configure Eccaffaan-m/ECC276k1 repos~2kAutomated safety check: PassMIT
Configure Eccaffaan-m/ECC276k—~1.3kAutomated safety check: PassMIT

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Questions about Setup P3

What does Setup P3 do?

Configure which models p3-stack uses per role and at what reasoning budget. Setup P3 is an agent skill from uzairansaruzi/p3-stack. Configure which models p3-stack uses per role and at what reasoning budget.

When should I use Setup P3?

Setup P3 fits situations like: configure p3 models; changing p3-stacks model choices.

How do I install Setup P3 in Claude Code?

Run `npx skills add uzairansaruzi/p3-stack --skill setup-p3 -a claude-code`. Or copy the skill folder (skills/setup-p3 in uzairansaruzi/p3-stack) into .claude/skills/setup-p3 in your project. Claude Code loads it when a task matches its description.

How do I install Setup P3 in Codex?

Run `npx skills add uzairansaruzi/p3-stack --skill setup-p3 -a codex`. Or copy the skill folder (skills/setup-p3 in uzairansaruzi/p3-stack) into .agents/skills/setup-p3 in your project. Codex loads it when a task matches its description.

Can I use Setup P3 in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add uzairansaruzi/p3-stack --skill setup-p3 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/setup-p3, .gemini/skills/setup-p3, .github/skills/setup-p3 and .opencode/skills/setup-p3 in your project.

What does Setup P3 need to run?

SKILL.md names no scripts, command-line tools or credentials: Setup P3 is instructions for the agent only.

Does Setup P3 access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Setup P3 safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Setup P3 use?

Setup P3 is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Setup P3 use?

About 1.5k tokens (SKILL.md is roughly 5.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Setup P3?

Skills that share tags, products or a category with Setup P3: Configure Channel (openclaw/openclaw, 392k stars), Configuration (BuilderIO/agent-native, 7.1k stars), Aria Roles (thedaviddias/Front-End-Checklist, 74k stars) and Configure Ecc (affaan-m/ECC, 276k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Setup P3?

uzairansaruzi (a GitHub user) maintains it in uzairansaruzi/p3-stack, which has 143 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 5, 2026.

Source: uzairansaruzi/p3-stack on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.