Prp Deliver

CommunityPopular

Wirasm

prp-deliver

This is an experimental skill. Never use it unless the user explicitly tells you to invoke /prp-deliver.

Overview

Publisher	Wirasm
Repository	`prp`
Skill name	`prp-deliver`
Stars	2.2K
Forks	607
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Wirasm on GitHub. Read the source before you install it.

Installation

Install the Prp Deliver AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Wirasm/prp.git /tmp/prp
mkdir -p .claude/skills
cp -r /tmp/prp/plugins/prp-core/skills/prp-deliver .claude/skills/prp-deliver

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prp Deliver in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Prp Deliver on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Prp Deliver is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Deliver to a Reviewed PR

Own one outcome from source input to a published READY TO MERGE review and green CI. Act as the sub-orchestrator for this delivery: start and steer specialist agents, preserve their handoff artifacts, and do not implement or review the work in this context.

Input: $ARGUMENTS (if absent, use the conversation).

Ownership contract

Continue autonomously through plan, implementation, PR, review, correction, re-review, and CI. A published report is observable progress, not a pause point.
Run stages sequentially in the delivery owner's checkout. Only one implementation or correction agent may mutate it at a time.
Use a fresh agent for planning, a fresh agent for implementation, and a fresh independent agent for every review. Resume the implementation agent for corrections while it remains available.
Keep the plan path, implementation report, PR, latest review report, publication URL, and agent handles. Durable artifacts—not recalled summaries—cross context windows.
Keep a verbatim caller-decisions record of two kinds: constraints that bind the whole delivery, such as scope, base, and product decisions; and dispositions attached to one finding or blocker. A constraint applies to every later stage. A disposition applies only to the finding it names, while that finding is live. Update the record when the caller resolves a blocker, and pass each fresh agent the constraints plus the dispositions its stage acts on, verbatim.
Carry the burden of proof. Prove completion with green validation, the live PR, the complete published review, its READY TO MERGE verdict, and green required CI.
Stop only when a product decision, missing prerequisite primitive, inaccessible dependency, permission boundary, or repeated no-progress failure cannot be resolved autonomously. Report the exact decision or access needed and a recommendation.
Do not merge the PR. The caller owns the merge gate.

1. Resolve and plan

Accept an issue or tracker URL, PRD, document, existing .plan.md, free-form request, conversation context, or reviewed PR.

Review-only request or contributor PR: use /prp-review; this is not a delivery run.
Existing plan: use it. If it is issue-derived and lacks a verified Plan Publication, start a planning agent with /prp-plan publish <absolute-path> first.
Issue whose plan was already published: let /prp-implement resolve it from source metadata and require that agent to return the persisted absolute plan path.
Existing PR with a published PRP review: resolve its plan and implementation report, then enter correction or review without repeating completed stages.
Otherwise start a fresh agent with this prompt:

Invoke /prp-plan against <complete input>. Additional caller context: <relevant context and explicit base, if any>. Caller constraints, verbatim: <constraints or "None">. Return the absolute plan path, source and publication URLs, and any concrete blocker.

Require an absolute plan path before review and, for issue-derived plans, a verified published-plan URL.

2. Implement and open the PR

Start a fresh agent in the same checkout with this prompt:

Invoke /prp-implement on <absolute plan path or source issue> with base <explicit base, if any>. Caller constraints, verbatim: <constraints or "None">. Own implementation through validation, scoped commit, PR creation, linked PRD updates, and the implementation report. Return VALIDATION: GREEN, the resolved absolute plan path, absolute report path, and PR URL; otherwise return the concrete blocker.

Do not begin review without VALIDATION: GREEN, a live PR, and the implementation report.

3. Review independently

Start a fresh agent with this prompt:

Invoke /prp-review on <PR URL or number> with scopes <requested scopes, if any>. Caller constraints, verbatim: <constraints or "None">. Publish the complete review to GitHub. Return the verdict, canonical review-report path, verified publication URL, and any review blocker.

Require the complete canonical review report, its absolute path, its complete GitHub publication, and the verified publication URL.

4. Correct and re-review until ready

For NEEDS FIXES, REVIEW INCOMPLETE, or any OPEN finding, send the complete review report—not an abbreviated finding list—to the implementation agent:

Continue this delivery by invoking /prp-implement in review-correction mode for <PR>. Read <plan>, <implementation report>, and the complete review at <review report>. Caller constraints and the dispositions for findings in this report, verbatim: <constraints and dispositions or "None">. Disposition every finding under the skill's fix-now, follow-up, and decline rules. Restore VALIDATION: GREEN and update the implementation report. Commit and push only when repository changes are required; for an evidence-only disposition, prove the PR head is unchanged.

Let the implementation agent disposition the report using its plan and code context. Prefer fixing valid, narrow, low-risk findings now; track only valuable distinct outcomes, and decline speculative or directionally wrong work without creating backlog noise.

If that agent is unavailable, start a fresh correction agent with the same complete artifact bundle. After every correction or disposition, start another fresh review agent with the caller constraints, the complete canonical report, and the dispositions under verification, then update the canonical publication. Repeat until READY TO MERGE with every finding terminal, or a genuine blocker survives without new evidence or progress. Do not wait for or check CI between rounds; CI clears once, at the end of the delivery, on the final head.

5. Require green CI

After READY TO MERGE, wait for every required CI check. A pending check is not green. Return a PR-caused failure and its complete evidence to the implementation agent and tell it to invoke /prp-implement in CI-correction mode, then run a fresh review against the changed head. When the repository has no required CI, rerun its authoritative local validation instead and record that evidence.

6. Return the outcome

Return the implemented outcome, absolute plan and implementation-report paths, PR URL, READY TO MERGE verdict, latest review-report path, GitHub publication URL, validation summary, and CI results. These are the proof the caller verifies before accepting the workstream. Only then suggest meaningful remaining non-blocking follow-ups. If genuinely blocked, return the same artifact bundle plus the exact blocker and recommended next action.

Frequently asked questions

What does the Prp Deliver AI skill do?

This is an experimental skill. Never use it unless the user explicitly tells you to invoke /prp-deliver.

Why use Prp Deliver on TypingMind?

Because you install it once and use it with any model. Prp Deliver is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Prp Deliver in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Wirasm/prp/tree/development/plugins/prp-core/skills/prp-deliver. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prp Deliver?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Prp Deliver?

As many as you like. As long as a model supports skills, you can use Prp Deliver with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prp Deliver AI skill free?

Yes. It is published on GitHub by Wirasm under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Deliver to a Reviewed PR

Ownership contract

1. Resolve and plan

2. Implement and open the PR

3. Review independently

4. Correct and re-review until ready

5. Require green CI

6. Return the outcome

Frequently asked questions

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