agentleFS
youdcodeyoudcode/open-company/.claude/skills/replies/SKILL.md

replies

Skill2 starsChanged 53 days agoMITView on GitHub

Reads the reply emails the human dropped into workspace/prospecting/inbox/ (.eml files), updates the leads, respects opt-outs, and summarizes what to do next. Use when the human types "replies".

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

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

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

    If nothing is in the inbox, explain how to add replies: save or drag the email as a .eml file into workspace/prospecting/inbox/ (Apple …

    line 12

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill 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
SKILL.md

Replies

Role: sales.

  1. node tools/replies.mjs --as sales. The script matches each reply to a lead, marks it replied (or do_not_contact if the person asked to stop), and adds the reply to the account file.
  2. If nothing is in the inbox, explain how to add replies: save or drag the email as a .eml file into workspace/prospecting/inbox/ (Apple Mail, Outlook, Thunderbird: drag the message into the folder; Gmail: "Download message").
  3. For each replied lead, read the reply in the account file and propose ONE next step to the human (answer draft, meeting brief, stop). Do not draft an answer before the human chooses.
  4. Unmatched replies: list the sender and ask the human which lead it belongs to.

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.