mcpField
A
aim

aim

github.com/lilmgeniusAgent workflows1.4k1.2k installsUpdated 4w ago
Repository

About aim

aim is an agent skill that infers a likely intent from supplied data and presents it as a proposal for confirmation. It grounds the proposal in what was read and avoids making the user formulate an intent from scratch.

Key features

  1. 01Read all supplied data before proposing
  2. 02State one evidence-based intent
  3. 03Suggest a next step
  4. 04Request confirmation or correction
  5. 05Stop when the data is insufficient

Use cases

  1. 01Turn handed-over material into a clear intent proposal
  2. 02Help confirm the likely goal behind a set of data

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/lilmgenius/paperthin --skill aim

After installing, type/aimin Claude Code to confirm it loaded.

Details

From the project README

Read the data and propose the intent behind it, for the user to confirm.

Goal

The result is a proposal the user only confirms, revises, or rejects — never a question. Asking makes the user compose a sentence they did not have ready; proposing lets them answer with a yes. If the turn ends with them writing that sentence anyway, the skill missed.

Workflow

  1. Read every piece of the handed-over data end to end before proposing anything.
  2. State the intent you read, in one line grounded in what the data actually shows.
  3. State briefly what you would do next on that intent.
  4. Ask only to confirm — right, wrong, or adjust.

Rules

  • Read before proposing. A proposal without reading is a guess.
  • Ground it in the data. Point at what you read, not what you assumed.
  • One intent per turn. If two are plausible, propose the likelier and name the other in a clause.
  • Confirm, don't compose. If the turn ends with the user assembling a sentence, redo the proposal.
  • If the data is too thin to propose from, say so and stop. Do not fall back to asking.

Verification

The user's next reply is short — a yes, a correction, or a small adjustment. If they had to explain what they wanted from scratch, the proposal was wrong, or was really a question in disguise.

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