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Goal Filter

Community
indranilbanerjee
goal-filter

Lock one primary goal per brand and judge ideas or drafts against it. "does this fit our goal"

Overview

Publisherindranilbanerjee
Repositorydigital-marketing-pro
Skill namegoal-filter
Stars
866
Forks
138
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Goal Filter 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.
    https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/goal-filter
  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/indranilbanerjee/digital-marketing-pro.git /tmp/digital-marketing-pro
mkdir -p .claude/skills
cp -r /tmp/digital-marketing-pro/skills/goal-filter .claude/skills/goal-filter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Goal Filter 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 Goal Filter 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 Goal Filter 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.

/digital-marketing-pro:goal-filter

The strategic filter. One goal is locked per brand; everything gets measured against it before time or budget is committed. Marketing fails quietly by doing good work toward nothing in particular — every piece defensible, the quarter's number missed anyway.

State

The locked goal lives in the brand workspace, so every session reads the same one:

~/.claude-marketing/brands/{brand-slug}/goal-lock.json
json
{
  "goal": "40 qualified demo bookings per month from organic + email",
  "metric": "demo bookings attributed to owned channels",
  "target": 40,
  "deadline": "2026-12-31",
  "locked_at": "2026-08-12",
  "history": [
    {"checked": "2026-08-14", "item": "podcast idea", "verdict": "OFF"}
  ]
}

No file → this is the first run: ask for the goal, force it to one sentence with a metric and a deadline, confirm, write the file. If the user names three goals, make them rank — the filter is useless with more than one.

Judging an item

Read the locked goal, read what the user brought, and rule honestly:

# Goal check — {the locked goal}

## What you brought
[One line]

## Verdict: ON GOAL / PARTIAL / OFF GOAL

## Why (2-3 sentences)
[Does this move the goal's metric? How directly? What is the opportunity cost —
what on-goal work does this displace?]

## The fix (if PARTIAL or OFF)
[The specific change that would make it serve the goal — or "park it", with
what to do instead]

## The sharper version (always)
[The same idea, rewritten to pull harder toward the metric]

Append the verdict to history in the state file.

Critical rules

  • ONE goal at a time. Multiple goals are a priority argument the user has not had yet. Force the ranking before locking anything.
  • Rule honestly. OFF GOAL is a legitimate verdict, and the filter is worthless if it rubber-stamps. An agency that never says "this doesn't serve your objective" is a vendor, not a partner.
  • Never just judge — always hand back an action. The fix or the sharper version, every time. The user leaves with something to do, not just a grade.
  • Name patterns across checks. The history is there to be read: three OFF verdicts in a week is not three isolated ideas, it is a drift — say so, and ask what is pulling attention off the goal. This is the filter's second job: the single verdicts protect the quarter, the pattern protects the strategy.
  • Goals are marketing outcomes — revenue, qualified leads, audience quality, authority in a niche, retention. "More followers" is accepted only with a because-clause that survives one round of "and what does that get you?".
  • Changing the goal is allowed, silently drifting is not. --set on an existing lock archives the old goal into history with its end date, so the quarter's record shows one deliberate change rather than a smear.
  • Engagement integration: inside a 12-Part engagement, the engagement's objectives are the goal source — offer to lock Part 1's primary objective rather than inventing a parallel one.

Frequently asked questions

What does the Goal Filter AI skill do?

Lock one primary goal per brand and judge ideas or drafts against it. "does this fit our goal"

Why use Goal Filter on TypingMind?

Because you install it once and use it with any model. Goal Filter 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 Goal Filter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/goal-filter. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Goal Filter?

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 Goal Filter?

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

Is the Goal Filter AI skill free?

Yes. It is published on GitHub by indranilbanerjee 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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