agentleFS
vinitjhawarvinitjhawar/opencouncil/skills/intake/SKILL.md

intake

Skill1 starsChanged 6 months agoMITView on GitHub

The one-question router. Asks the user light, medium, or heavy and returns the chosen intensity to clone. Always asks every time unless the user has explicitly set a remembered default with the "remember" or "always" commands.

34 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use plan, triage and 7 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • BlockSkill

    plan

    Draft a TDD, PRD, or lightweight plan in the conversation without committing it.

    Also in 4 projects that use this

  • Google CloudSkill

    triage

    Gather context on a change or bug and plan the implementation.

    Also in 4 projects that use this

  • AWSSkill

    retro

    Conduct a retrospective on a coding session.

    Also in 4 projects that use this

  • Microsoft AzureSkill

    build

    Build the TypeSpec Rust emitter from source. Run this after cloning the repo, after pulling changes, or when TypeScript source files have been modified.

    Also in 3 projects that use this

  • VercelSkill

    deploy

    Deploy applications to Vercel. Use when the user says "deploy", "deploy to Vercel", "push to production", "deploy my app", or "go live".

    Also in 3 projects that use this

  • Microsoft AzureSkill

    verify

    End-to-end app testing pipeline for browser-based web apps on cloud browsers via Azure Playwright Workspaces: verify the live app, author tests for working flows, heal failing tests, then re-run with video and produce one consolidated report. Three phases (app verification, test authoring, test healing) plus a scoped final sanity run; each phase emits a sub-report. Use when asked to "verify my app", "make sure my app works and has good test coverage", "do a full QA pass", "add tests where I'm missing coverage", "fix failing tests and add new ones", "smoke test before deploy", "QA my deployment", or any combined verify-and-test ask. Requires Azure CLI (`az login`) and a Playwright Workspace resource ID — bootstraps configs on first invocation. Browser-based web apps with Playwright only — not for unit/API tests, native mobile/desktop, load/perf, or full accessibility audits.

    Also in 4 projects that use this

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 33 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If a default exists, intake skips the question and uses that default.

    line 60
  2. Distinctive:

    If no default exists (the user has never said "remember"), intake always asks.

    line 62
  3. Very specific:

    When the user explicitly sets a default, write to ~/.opencouncil/preferences.json:

    line 66

“Common” is measured: kept by at least 6 in 10 of the 33 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Intake

One question. Three answers. Done.

The prompt

task received. pick intensity:

light    5 board members, no debate, no employees, no loops
         best for: captions, replies, quick decisions
         ~30 seconds, ~8k tokens

medium   10 employees draft  +  10 board review  +  1 revision loop
         best for: posts, emails, drafts, plans
         ~2 minutes, ~25k tokens

heavy    employees meet  +  full board debate  +  up to 3 revisions
         best for: launches, contracts, CVs, anything irreversible
         ~5 minutes, ~45k tokens

reply: light, medium, or heavy

What each mode actually runs

EmployeesBoardMeetingRevision loopsTimeTokens
light05no0~30s~8k
medium3 to 5 picked by clone10no1~2min~25k
heavyall 10 (if relevant)10yesup to 3~5min~45k

In medium and heavy modes, clone picks which employees attend based on the task. A LinkedIn post pulls Writer + Growth + Researcher. A bug fix pulls Engineer + PM. A cover letter pulls Career Agent + Writer. See the employees index for the full roster.

Reply parsing

Accept any of: light, l, 1 → light. medium, m, 2 → medium. heavy, h, 3 → heavy. Case-insensitive. Whitespace ignored.

Memory behaviour (important)

Default: always ask, every single time. Intake never auto-prompts "do you want to remember this?" after a run. The question is asked fresh on every task.

A remembered default is set ONLY when the user explicitly says so. Recognised commands:

User saysEffect
remember thisSaves the just-picked mode as the default
remember lightSaves light as the default
remember mediumSaves medium as the default
remember heavySaves heavy as the default
always heavySame as remember heavy
forget my defaultClears the saved default, back to asking every time
forgetSame as above

If a default exists, intake skips the question and uses that default. Override for one run only with heavy this time, light this time, or medium this time (does not change the saved default).

If no default exists (the user has never said "remember"), intake always asks.

Storage

When the user explicitly sets a default, write to ~/.opencouncil/preferences.json:

{ "default_intensity": "medium", "set_by_user_at": "2026-05-17T13:50:00Z" }

The set_by_user_at field exists to make it clear this was a deliberate user action, not an auto-remember.

Reset

opencouncil reset clears the stored default and any other preferences. Same as forget my default.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.