agentleFS
AgiFlowAgiFlow/ai-plugin/skills/daily-standup/SKILL.md

daily-standup

Skill4 starsChanged 33 days agoMITView on GitHub

Produce a concise read-only Agiflow status summary covering completed work, work in progress, blockers, and recommended next priorities. Use for daily standups, morning checks, stakeholder updates, or a quick project pulse.

16 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 3 are distinctive, and 6 are very specific to this project.

  • 0

    Common

    Most of the 11 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 6

    Very specific

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

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

    Call get_current_scope and resolve the requested project when needed.

    line 12
  2. Very specific:

    Call list_active_tasks_by_org for current active work.

    line 13
  3. Very specific:

    Call list_work_units for active and blocked work units.

    line 14
  4. Very specific:

    Call get_project_detail when the summary is project-specific.

    line 15
  5. Very specific:

    Call list_members to resolve assignee context.

    line 16
  6. Very specific:

    Call get_task, get_work_unit_progress, or list_task_comments only when needed to confirm progress or a blocker.

    line 17
  7. Distinctive:

    Use short sections titled Done, In Progress, Blocked, and Next Up.

    line 33
  8. Distinctive:

    Do not claim an item changed recently unless the returned data supports that conclusion.

    line 38
  9. Distinctive:

    Keep the summary scannable and end with one clear recommendation.

    line 40

“Common” is measured: kept by at least 6 in 10 of the 11 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

Agiflow Daily Standup

Give a brief, evidence-based project pulse. Do not modify workspace data.

Workflow

  1. Call get_current_scope and resolve the requested project when needed.
  2. Call list_active_tasks_by_org for current active work.
  3. Call list_work_units for active and blocked work units.
  4. Call get_project_detail when the summary is project-specific.
  5. Call list_members to resolve assignee context.
  6. Call get_task, get_work_unit_progress, or list_task_comments only when needed to confirm progress or a blocker.
  7. Summarize:
    • Done or moved to Review since the latest available update
    • Current work in progress
    • Blocked or stalled items
    • Highest-priority next actions

Priority Logic

  1. Resolve blockers that prevent other work.
  2. Finish existing work in progress before starting more work.
  3. Select the highest-priority ready item.
  4. Recommend refinement when a task is not ready.

Output Format

Use short sections titled Done, In Progress, Blocked, and Next Up. Include task or work-unit identifiers when available. State clearly when no recent changes or blockers are found.

Guardrails

  • Remain read-only. Do not call mutation tools.
  • Do not claim an item changed recently unless the returned data supports that conclusion.
  • Distinguish confirmed blockers from possible signs of stalled work.
  • Keep the summary scannable and end with one clear recommendation.

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.