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multi-deliverable-tracking

Track tasks that require several outputs by listing every deliverable, updating a visible checklist, and verifying that each result exists. Helps prevent work from ending while requested files, reports, or other outputs remain unfinished.

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Track and complete all required deliverables before finishing a task

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适用场景

  • Tracking several files requested in one task
  • Managing progress across multiple reports
  • Checking all outputs before closing a task

包含的文件(2)

  • SKILL.md5.6 KB
  • .skill_id40 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Multi-Deliverable Task Completion

Purpose

Ensure ALL required outputs are completed before concluding a task, preventing premature task termination when multiple deliverables are required. This skill includes mandatory enforcement steps that MUST be followed.

Core Workflow

Step 1: Identify All Deliverables Upfront

CRITICAL: You MUST complete this step before producing ANY deliverable or taking any other action.

At task start, explicitly enumerate EVERY required output:

  • Parse task requirements carefully for action verbs: "create", "generate", "produce", "deliver", "write", "send"
  • Count distinct deliverables (files, reports, emails, code modules, analyses, etc.)
  • Document this list visibly in working notes
  • Note any dependencies between deliverables

MANDATORY OUTPUT FORMAT: Before any other work, output this exact format:

DELIVERABLES_IDENTIFIED:
1. [filename/description] - [brief description]
2. [filename/description] - [brief description]
...
TOTAL_DELIVERABLES: N

Example identification:

Required Deliverables:
1. [ ] Email to Juvoxa CEO
2. [ ] Follow-up analysis report
Total: 2 deliverables

Step 2: Create a Completion Tracker

CRITICAL: This tracker MUST be created and visible throughout task execution.

Maintain a visible checklist throughout task execution:

DELIVERABLE TRACKER
===================
[ ] Deliverable 1: [brief description]
[ ] Deliverable 2: [brief description]
[ ] Deliverable 3: [brief description]

Completed: 0/3

Update this tracker AFTER each deliverable is fully completed (not just started).

Step 2.5: Filesystem Verification [MANDATORY BEFORE COMPLETION]

Before considering any deliverable complete, verify it exists:

  • For file deliverables: Use list_dir or run_shell (ls/cat) to confirm the file exists
  • For output deliverables: Verify the output was actually produced in the response stream
  • Document verification with: [✓] filename verified in filesystem

Step 3: Work Through Deliverables Systematically

  • Complete each deliverable fully before marking it done
  • Update the tracker immediately after completion
  • If a deliverable fails, note the failure but continue to others if possible
  • Return to failed items after completing others

Step 4: Final Verification Before Stopping

Before concluding the task, run this mandatory checklist: CRITICAL ENFORCEMENT: You are BLOCKED from outputting <COMPLETE> until this verification passes.

FINAL VERIFICATION (REQUIRED BEFORE <COMPLETE>)
==================
1. Review original task requirements
2. Count total deliverables identified: ___
3. Count deliverables marked complete: ___
4. Do counts match? YES/NO
5. If NO: Identify missing deliverables and complete them
6. If YES: Verify each deliverable exists and meets quality standards
7. Filesystem verification (REQUIRED):
   - [ ] file1.ext: VERIFIED (list_dir/run_shell confirmed)
   - [ ] file2.ext: VERIFIED (list_dir/run_shell confirmed)

**BLOCKING RULE:** If counts do not match OR any file cannot be verified in the filesystem, you MUST:
1. NOT output <COMPLETE>
2. Identify the missing/unverified deliverables
3. Complete and verify them
4. Re-run this verification checklist

**Only output <COMPLETE> when all deliverables are verified present in the filesystem or output stream.**

Only stop when all deliverables are verified complete.

Step 5: Self-Check Questions

Before marking task complete, ask:

  • "Did I create EVERY output the task requested?"
  • "Are there any deliverables I started but didn't finish?"
  • "Would someone reviewing my work see all required outputs?"
  • "Have I verified EACH deliverable exists in the filesystem using list_dir or run_shell?"
  • "Is my DELIVERABLES_IDENTIFIED output present and accurate?"

Common Pitfalls to Avoid

❌ Stopping after first deliverable - Just because one output is done doesn't mean the task is complete ❌ Stopping after first deliverable - Just because one output is done doesn't mean the task is complete

❌ Outputting <COMPLETE> without filesystem verification - You must verify files exist before completion

❌ Skipping DELIVERABLES_IDENTIFIED output - This mandatory output must appear before any work begins

❌ Assuming implicit completion - Don't assume related outputs are "part of" a main deliverable unless explicitly stated

❌ Losing track mid-task - The tracker must stay visible and updated throughout

❌ Counting drafts as complete - Only mark done when the deliverable meets quality standards

Code Example: Tracker Template

# Deliverable tracking template
deliverables = {
    "email_to_ceo": {"status": "pending", "file": "ceo_email.txt"},
    "analysis_report": {"status": "pending", "file": "analysis.pdf"},
    "summary_doc": {"status": "pending", "file": "summary.docx"},
}

def mark_complete(name):
    deliverables[name]["status"] = "complete"
    print(f"✓ {name} completed")
    print(f"Progress: {sum(1 for d in deliverables.values() if d['status'] == 'complete')}/{len(deliverables)}")

def all_complete():
    return all(d["status"] == "complete" for d in deliverables.values())

When to Apply This Skill

Use this pattern whenever a task involves:

  • Multiple files to create
  • Several analyses or reports
  • Multiple communications (emails, messages)
  • Code with multiple modules/components
  • Any task with enumerated requirements (1), 2), 3)...)

Remember

The task is NOT complete until ALL deliverables are complete. One done ≠ all done.

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