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Ce Pov

OrganizationPopular
EveryInc
ce-pov

Judge a supplied subject against the project's evidence and constraints. Use when assessing an external-adoption question, a holistic take on a document, or a supplied approach set. Use for an oracle panel to consult other models and reconcile their opinions. Use ce-explain for understanding and ce-doc-review for findings review.

Overview

PublisherEveryInc
Repositorycompound-engineering-plugin
Skill namece-pov
Stars
25.1K
Forks
2.1K
Bundled files
15
LicenseMIT
Links
  • 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.

  • 15 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by EveryInc on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/EveryInc/compound-engineering-plugin.git /tmp/compound-engineering-plugin
mkdir -p .claude/skills
cp -r /tmp/compound-engineering-plugin/skills/ce-pov .claude/skills/ce-pov
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ce Pov 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 Ce Pov 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 Ce Pov 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.

Form a Point of View

Produce a decisive, project-grounded point of view in the subject's own shape: a graded verdict on an external-adoption question, a holistic take on a document, or a position on a supplied approach set. The subject is whatever this skill was invoked with, in the prompt or the conversation. Stay read-only while forming and reconciling the POV. You are done when the POV is delivered with its attribution and required disclosure, or when an explicit blocker is returned. Use ce-bakeoff to develop competing solutions, ce-ideate to explore opportunities, or ce-brainstorm to establish goals. The year is 2026, for source recency.

Grounding is not optional

Never issue a POV you did not earn against the project's own context. Every subject must meet the minimum project evidence (the project floor) in references/method.md. An external-adoption verdict must also meet the full external evidence bar there. A document or approach-set POV must verify against outside sources any external claim its bottom line depends on. Nothing the conversation asserts substitutes for grounding.

Consumer and interaction

Deliver a supported position in the form the intended consumer can use. Lead with the decision and preserve the evidence, material tradeoffs, uncertainty, and conditions that determine it. Make identifiers understandable without requiring the reader to reopen the subject. A person's request may need a brief answer or a shareable document; another workflow may need a decision embedded in its own work.

When contributing to an ongoing workflow, return the result and leave continuation to its owner, the calling workflow. Do not add follow-up or panel offers to that return. An explicit oracle or named-peer request still runs the panel, including when it comes from a calling workflow.

Identify the question and return the result

Identify the question from the request and conversation, then look up facts you can verify. Do not interview the user to work out what to assess. If missing information would change the recommendation and you cannot find it, return Blocked — missing context. Explain what is missing, why it matters, and what would resolve it. The calling agent decides whether to ask for clarification or take another action. This applies whether the user invokes ce-pov directly or another agent calls it; no separate non-interactive mode is needed.

Artifact Root

Resolve <root> the first time you compose a <root>/ path; a read of <root>/solutions/ counts as composing one. Pass the resolved path to scouts, never the config. A non-git project has no <root>, so its prior-decision scan uses local ADRs and design docs instead.

Resolve the CE artifact root <root> before composing any artifact path.

  • Read docs_root from <repo-root>/.compound-engineering/config.yaml only (<repo-root> = git rev-parse --show-toplevel). Do not read it from config.local.yaml. Unset -> <root> is docs, exactly as before.
  • Validate a set value: a repo-relative directory whose real, symlink-resolved path stays inside the repo and is neither the repo root nor under .git/. Otherwise stop with an error naming docs_root and the value -- never fall back to docs.
  • Use <root> as the sole artifact location: create it if absent, compose each path as <root>/<subdir> with this skill's own subdirectory, and never also read docs.

Phase 0: Frame and Classify

Read references/intake.md now, before any grounding. It defines the output mode, what a calling workflow passes in, orientation and framing, sizing, and what to do when the question has no bounded answer. Settle the subject and the POV intent there (adopt / migrate / compare / is-this-our-problem / Document-take / Approach-set / explainer); an intent that belongs to another skill finishes at intake, and one that continues records how reversible the decision is. Read references/boundaries.md when this skill's fit is in doubt.

Phase 1: Ground

Read references/grounding.md now, before grounding by either path. It defines the model tiers (the POV reasoning itself is never dispatched), where scratch files may go, what scouts receive and how many run, which capabilities gate which steps, and how grounded facts are kept apart from unconfirmed ones.

Send scouts directly to candidate-specific current evidence, never a generic repo profile. They search in their own context and return a dossier path plus a gist, which you read on demand. Where the facts the verdict depends on are already located, confirm them with bounded reads of the authoritative source instead of dispatching scouts; unscoped or noisy grounding still dispatches. A claim made in the conversation is a pointer to check, never self-verifying. The prior-decision scan (<root>/solutions/, ADRs, design docs) stays mandatory on either path.

When the judgment requires an explanation of unresolved behavior or design rationale, invoke ce-explain. Pass the question, its scope, and the decision it informs. Use adequate current evidence instead of repeating an investigation. Treat its cited findings as evidence to assess under the same grounding standard, not as authority for the recommendation. Keep ownership of the judgment here. If ce-explain is unavailable, gather the evidence directly or report what is missing.

Phase 2: Verify Grounding

Read references/method.md now, before reasoning about the POV. It defines the Verify and POV steps, the skeptic stance, tiering, and the evidence check. Apply that check over the grounded evidence. If the evidence falls short, no subject shape may return a confident result; that reference names the result each shape returns instead.

Phase 3: Point of View

First form ce-pov's own independent POV under the active subject-shape contract in references/method.md, but do not emit it. Freeze that position. Keep it out of an independent peer's initial context; expose it only when the task is to critique that position, or in a later reconciliation round.

A panel request is an explicit ask to consult or reconcile other models: a panel, a cross-check, or oracle, anywhere in the invocation context. Declining one, or merely mentioning one, is not a request. When a panel is requested, or when a POV formed without one may qualify for a proactive offer, read references/cross-model-panel.md before resolving participation or deciding whether to offer. Finish the panel branch before composing the result. A POV that follows a panel request states which peers ran, or that none did and why. A POV with no panel request carries no panel note.

Only then deliver the position with the content required by references/method.md. Adapt its presentation to the intended use; cite supporting evidence rather than reprinting dossiers or raw peer output.

Phase 4: Deliver and return

The judgment is the deliverable; implementation is not. A calling workflow receives the result and control back. For a requested write-up or continuation, read references/followup.md; it defines artifact delivery and what authority a downstream action needs. Do not require a next-step choice to complete a POV.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ce Pov AI skill do?

Judge a supplied subject against the project's evidence and constraints. Use when assessing an external-adoption question, a holistic take on a document, or a supplied approach set. Use for an oracle panel to consult other models and reconcile their opinions. Use ce-explain for understanding and ce-doc-review for findings review.

Why use Ce Pov on TypingMind?

Because you install it once and use it with any model. Ce Pov 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 Ce Pov in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/EveryInc/compound-engineering-plugin/tree/main/skills/ce-pov. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ce Pov?

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 Ce Pov?

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

Is the Ce Pov AI skill free?

Yes. It is published on GitHub by EveryInc 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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