agentleFS
tmussertmusser/context-to-action-skills/skills/follow-up-draft/SKILL.md

follow-up-draft

Skill2 starsChanged 59 days agoMITView on GitHub

Draft concise Slack or email follow-ups from context, notes, actions, or open asks.

The file

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 7 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    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. Distinctive:

    Do not send the draft unless explicitly asked.

    line 31
  2. Distinctive:

    Keep the message concise and workplace-user friendly.

    line 34
  3. Distinctive:

    Use only the useful subset of source-backed facts, assumptions, source gaps, stakeholder sensitivities, potential misreads, and the …

    line 38
  4. Distinctive:

    Use the smallest useful output.

    line 40
  5. Distinctive:

    When consuming upstream state, do not promote an assumption, inference, open question, proposed action, or stakeholder position into a …

    line 42
  6. Distinctive:

    Keep unresolved approvals, owners, timing, and blockers explicit or conditional in the draft.

    line 45
  7. Distinctive:

    Do not send, publish, update tickets, create events, or mutate systems unless explicitly asked.

    line 46
  8. Very specific:

    If the user wants a fuller record before drafting, use the optional CONVERSATION_STATE.md template from this pack when it is available.

    line 55

≈ “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

follow-up-draft

Purpose

Draft a concise follow-up that preserves the ask, owner, timing, context, and next step.

Use For

  • Post-meeting follow-ups
  • Slack reminders
  • Email recaps
  • Nudges on open asks

Inputs

  • Notes
  • Action list
  • Open ask
  • Project context
  • Prior thread context
  • A reduce-to-facts ledger or conversation-state record

Guardrails

  • Read before write.
  • Do not send the draft unless explicitly asked.
  • Include the ask, owner, deadline or timing, and next step when known.
  • Label assumptions or missing details.
  • Keep the message concise and workplace-user friendly.

Portable Output Contract

  • Use only the useful subset of source-backed facts, assumptions, source gaps, stakeholder sensitivities, potential misreads, and the suggested next action.
  • Use the smallest useful output.
  • Label assumptions and preserve source gaps, source anchors, and confidence labels.
  • When consuming upstream state, do not promote an assumption, inference, open question, proposed action, or stakeholder position into a fact, decision, commitment, owner, or deadline without new source support.
  • Keep unresolved approvals, owners, timing, and blockers explicit or conditional in the draft.
  • Do not send, publish, update tickets, create events, or mutate systems unless explicitly asked.

Output

  • Direct version
  • Warm version
  • Executive concise version
  • Context note, when helpful

If the user wants a fuller record before drafting, use the optional CONVERSATION_STATE.md template from this pack when it is available.

Success Standard

The user should be able to copy, tweak, and send a version within 5 minutes.

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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.