agentleFS
philpalmieriphilpalmieri/engineering-manager-skills/skills/management/direct-report-prep/SKILL.md

direct-report-prep

Skill1 starsChanged 6 months agoMITView on GitHub

Prepare coaching-oriented 1:1 talking points for a direct report. Gathers GitHub activity, vault context, and open follow-ups to build structured prep notes. Use when prepping for a 1:1 with someone you manage.

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 4 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If ambiguous (multiple matches), ask the user to clarify

    line 31
  2. Distinctive:

    Check last 5-7 daily notes (both active and archive) for:

    line 52
  3. Very specific:

    Write directly into People/{vault_name}.md, prepended before the most recent existing entry.

    line 73
  4. Distinctive:

    Before writing (unless the user said "just do it"), present a brief summary:

    line 92
  5. Very specific:

    Wikilink to project files: when referencing projects: [[Projects/Project Name]]

    line 100
  6. Very specific:

    Wikilink to people: when referencing other team members: [[People/Name]]

    line 101
  7. Distinctive:

    Idempotent: If today's date entry already exists in the People file, update it rather than creating a duplicate.

    line 103

≈ “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

Direct Report 1:1 Prep

Prepare talking points for a 1:1 with a direct report. Combines GitHub activity data with vault context (People file, recent dailies) to generate coaching-oriented prep.

When to use

  • "Prep 1:1 for [name]", "prep directs", "1:1 prep for [name]"
  • As part of the prep-my-day orchestration skill

Prerequisites

  • Team roster (team.json) with the person listed under members with relationship: "direct"
  • A People file for the person in the vault's People/ directory
  • GitHub CLI (gh) authenticated with access to the org

Process

Step 1: Identify the person

  1. Match the requested name to a member in the team roster using name, login, or vault_name
  2. Confirm the person has "relationship": "direct"
  3. If ambiguous (multiple matches), ask the user to clarify

Step 2: Gather data

From the vault:

  • Read People/{vault_name}.md for:
    • Open todos (- [ ]) from previous entries
    • Recent 1:1 notes and recurring themes
    • Items tagged #feedback or #followup
    • Stale items (open tasks with dates older than 2 weeks)
    • Items with ⏫ or 📅 markers (high priority or time-sensitive)

From GitHub (last 7 days):

gh search prs --author={login} --org={org} --created={7_days_ago}..{today} --json number,title,repository,state,mergedAt
gh search prs --author={login} --org={org} --merged={7_days_ago}..{today} --json number,title,repository,mergedAt

Extract: PR number, title, repo, state, merged date. Note volume and breadth.

From recent dailies:

  • Check last 5-7 daily notes (both active and archive) for:
    • Mentions of the person's name or vault link
    • Open action items involving them
    • Context from previous discussions

Step 3: Build talking points

Organize into these categories:

Recognition — Always lead with something positive if there's signal. Name specific PRs, review quality, initiative shown. Don't be generic ("great work this week"). Be specific ("the refactor in PR #1234 was clean, especially the test coverage").

Open follow-ups — Reference existing open tasks from prior entries that are still incomplete. Mention when they were first noted. Do NOT recreate them as new - [ ] checkboxes (the People file's DataviewJS query already surfaces open tasks).

Project status — For active projects the person is working on, check PR activity and note current state. Frame as check-in questions, not status demands. "How's the migration going?" not "Why isn't the migration done?"

Coaching opportunities — If a PR or pattern suggests a growth area, frame it as a question. "The refactor PR is solid; have you thought about how to test the migration path?" Not "You should test the migration path."

Feedback items — Any #feedback tagged items should be surfaced with context.

Step 4: Write to People file

Write directly into People/{vault_name}.md, prepended before the most recent existing entry.

Format:

#### [[Dailies/YYYY-MM-DD|YYYY-MM-DD]] 1:1

**Topic Name** (Context Type)
- Brief context or PR links
- Check in: question about the topic

**Another Topic** (Recognition)
- What they shipped and why it matters
- Call out: specific good work here

Context types: (Recognition), (Follow-up), (Project Status), (Coaching), (Feedback)

Step 5: Present summary

Before writing (unless the user said "just do it"), present a brief summary:

For [Name]: found N open PRs on [project], M stale follow-ups from [dates], and they merged [notable work] yesterday. Want me to write this up?

Rules

  • Do NOT create new - [ ] checkboxes in prep notes. People files typically have a DataviewJS query that aggregates open tasks. New checkboxes create duplicates. Use plain bullets instead.
  • Use bold for topic headings, not markdown heading levels (h1-h3 are reserved for file structure).
  • Wikilink to project files when referencing projects: [[Projects/Project Name]]
  • Wikilink to people when referencing other team members: [[People/Name]]
  • Include GitHub PR/issue links inline for quick reference during the meeting.
  • Idempotent: If today's date entry already exists in the People file, update it rather than creating a duplicate.
  • This is coaching prep, not status tracking. Frame everything through a development lens.

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.