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elicitlyelicitly/demos/AGENTS.md

demos

AGENTS.md1 starsChanged 36 days agoMIT-0View on GitHub

Guidance for AI coding agents (and humans) changing this repo. Do not create CLAUDE.md; this repo uses the AGENTS.md standard. Agent Skills (spec) that demonstrate Elicitly's tools with fixed sample data. They are references to copy and adapt, not integrations. The tools themselves are documented at <https://www.elicitly.ai/docs/tools/>; check a skill's tool calls against that reference, not against memory. skills/<name>/ holds SKILL.md plus assets/: - Frontmatter: name (matches the folder), description, license: MIT-0, and compatibility naming the edition and tools ("Elicitly…

  • Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.

    Of the AGENTS.md files we read, the 31,439 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.

  • In this repository7 other files it gives its agents.

The file

We split this AGENTS.md into the rules it gives an agent

5 rules. About 0 are common, 1 is distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

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

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

    Pro review tools: follow one loop: create → give the user reviewUrl → elicit_await until not pending → elicit_result → act on decision.

    line 25
  2. Very specific:

    Demos only: Every description starts "Elicitly demo".

    line 34
  3. Very specific:

    Every SKILL.md frontmatter parses as YAML and name matches its folder.

    line 61
  4. Very specific:

    Every template renders with LiquidJS against its sample data, with jsTruthy: true and outputEscape: "escape", which Elicitly uses.

    line 66
  5. Distinctive:

    Run the skill once in a host: a display in one that renders MCP Apps, a dialog in one that renders form elicitation (see the Support …

    line 69

≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “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
AGENTS.md

AGENTS.md — Elicitly demos

Guidance for AI coding agents (and humans) changing this repo. Do not create CLAUDE.md; this repo uses the AGENTS.md standard.

What this repo is

Agent Skills (spec) that demonstrate Elicitly's tools with fixed sample data. They are references to copy and adapt, not integrations. The tools themselves are documented at https://www.elicitly.ai/docs/tools/; check a skill's tool calls against that reference, not against memory.

A skill

skills/<name>/ holds SKILL.md plus assets/:

  • Frontmatter: name (matches the folder), description, license: MIT-0, and compatibility naming the edition and tools ("Elicitly Free or Pro (elicit_display) …" or "Requires Elicitly Pro (elicit_approval, …)") plus any origin to allow.
  • Templates (*.liquid) and sample data (*.json) live in assets/, and SKILL.md tells the agent to pass them verbatim. Keep layout out of the model's hands.
  • Pro review tools follow one loop: create → give the user reviewUrl → elicit_await until not pending → elicit_result → act on decision. Never act on a chat claim of approval.
  • Dialogs (elicit_confirm, elicit_form) handle all three outcomes: yes, an explicit no, and no answer (null / error). No answer never means yes.

Rules

  • Demos only. Every description starts "Elicitly demo". A demo with made-up business data says so ("Elicitly demo (sample data, …)") and ends "Use only when the user asks for … the <name> demo", naming its sample entity (Brightwater, Harbor, Larkspur): it must never trigger on a real-world request and answer it with sample data. (Jupiter, with real public facts, may trigger more broadly.) Each SKILL.md keeps the Demo note under its heading, and the step that would act says "In a real skill, … would happen here."
  • Made-up business data. Invent companies, people and figures; never use real customers or real people's names. Images committed here must be openly licensed and credited on the card. The salespeople photos are licensed stock that stays hosted on www.elicitly.ai, not committed here.
  • Keep the README in sync. A new or renamed skill updates the demos table (Demo, Tools, Edition, Try saying). Free demos first, and the "Try saying" prompt must match the description's trigger.
  • Accessibility (rendered output). WCAG 2.2 AA: text ≥ 4.5:1 contrast, images with alt, keyboard-reachable scrolling regions, and motion-reduce: variants for any animation.
  • Review-page templates (displayTemplate, rowTemplate, …) use plain HTML and a <style> block; give links target="_blank". Display templates may load DaisyUI and Tailwind from jsDelivr.
  • Conventional Commits (feat:, fix:, docs:, …).
  • Never commit or push without explicit user approval. Show the diff first.

Checking a change

  • Every SKILL.md frontmatter parses as YAML and name matches its folder. Watch for : (colon, space) inside an unquoted value such as description: YAML reads it as a new key and the skill fails to load. Rephrase, or quote the whole value.
  • Every assets/*.json parses.
  • Every template renders with LiquidJS against its sample data, with jsTruthy: true and outputEscape: "escape", which Elicitly uses.
  • Run the skill once in a host: a display in one that renders MCP Apps, a dialog in one that renders form elicitation (see the Support Matrix), and Pro skills against the hosted server.

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.