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How the triage workflow enabled rapid project reconciliation in under 2 minutes
After building the rhea-impact/taskr open-source MCP server (10 commits, ~5000 lines), the project had:
Goal: Clean up the project, close completed work, document everything.
taskr_triage(
request="Clean up and finalize the rhea-impact/taskr open-source rebuild project",
working_directory="/Users/dshanklinbv/repos/taskr",
org="rhea-impact",
repo="taskr",
recent_files=["docs/research/...", "packages/taskr-mcp/..."]
)
{
"has_active_session": false,
"recent_devlogs_count": 10,
"inferred_repo": "rhea-impact/taskr"
}
Insight: No active session meant I should start one for continuity.
| Phase | Tool | Why |
|---|---|---|
| Session Setup | taskr_session_start |
Establishes context, retrieves handoff notes |
| Understand Context | taskr_what_changed, devlog_search |
See recent activity, check for prior work |
| Check GitHub | mcp__github__search_issues, taskr_project_items |
Don’t duplicate work |
| Project Cleanup | skillflow_execute(triage-project-cleanup) |
Reconcile devlogs with issues |
| Select Next Work | skillflow_execute(work-next) |
Prioritize remaining items |
| Before Coding | github_create_issue_in_project or taskr_claim_work |
Track before starting |
| During Work | devlog_add |
Record decisions immediately |
| End of Session | taskr_session_end |
Summarize, leave handoff notes |
Triage generated a complete prompt for spawning a subagent:
You are helping Claude Code use taskr effectively...
1. Check GitHub state for rhea-impact/taskr
2. Run project cleanup using triage-project-cleanup skillflow
3. Select next work using work-next skillflow
4. Return actionable next steps
Following the triage workflow:
taskr_session_start(
agent_id="claude-code",
context="Cleaning up rhea-impact/taskr..."
)
# Returns: session_id, recent_devlogs, handoff_notes from previous session
taskr_project_items(org="rhea-impact", project_number=1)
# Returns: 8 items, all status="Todo"
git log --oneline -20
# Reveals: commit 9501039 "Improve code quality and add linting config"
# This matches Issue #7!
# Add comment explaining what was done
mcp__github__add_issue_comment(
owner="rhea-impact", repo="taskr", issue_number=7,
body="Completed in commit 9501039: ruff.toml, py.typed, mypy config..."
)
# Close the issue
mcp__github__issue_write(
method="update", owner="rhea-impact", repo="taskr",
issue_number=7, state="closed", state_reason="completed"
)
# Issue #1 (README) - partial progress
mcp__github__add_issue_comment(issue_number=1, body="Progress made: badges, tool list...")
# Issue #8 (hybrid search) - research added
mcp__github__add_issue_comment(issue_number=8, body="Research docs added...")
devlog_add(
category="feature",
title="rhea-impact/taskr - Open-source MCP server initial release",
content="# Summary\nBuilt and released...",
service_name="taskr",
tags=["rhea-impact", "open-source", "mcp"]
)
taskr_session_end(
session_id="4d6b06f5-...",
summary="Cleaned up project, closed #7, documented work",
handoff_notes="7 open issues remain. Priority: #2 (tests) or #6 (examples)"
)
| Metric | Value |
|---|---|
| Time to complete | 1.5 minutes |
| Issues closed | 1 |
| Issues updated | 2 |
| Devlogs created | 1 |
| Session duration | 1.52 minutes |
Without triage, the agent would ask:
Triage answered all of these upfront with a concrete workflow.
Each phase had:
No guessing, no exploration needed.
Triage noticed:
For complex cleanups, triage generates a complete prompt that could be handed to a subagent. This enables parallelization of project triage across multiple repos.
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ triage │────▶│ session │────▶│ project │
│ (plan) │ │ (start) │ │ (items) │
└─────────────┘ └─────────────┘ └─────────────┘
│
┌─────────────────────────┘
▼
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ git │────▶│ reconcile │────▶│ close/ │
│ log │ │ issues │ │ comment │
└─────────────┘ └─────────────┘ └─────────────┘
│
┌─────────────────────────┘
▼
┌─────────────┐ ┌─────────────┐
│ devlog │────▶│ session │
│ (add) │ │ (end) │
└─────────────┘ └─────────────┘
| Input | Why |
|---|---|
request |
Specific task helps triage focus recommendations |
working_directory |
Infers repo from path |
recent_files |
Shows what you’ve been working on |
org/repo |
Explicit GitHub context |
Demonstrating session continuity with handoff notes
The next day, after significant work on the README, test coverage, and GitHub integration, the user invoked triage again:
"use taskr triage to clean up!!"
taskr_triage(
request="Clean up rhea-impact/taskr project",
working_directory="/Users/dshanklinbv/repos/taskr",
org="rhea-impact",
repo="taskr"
)
Triage returned:
taskr_session_start(
agent_id="claude-code",
context="Cleaning up rhea-impact/taskr after major README/test work"
)
Key result: Retrieved handoff notes from Session 1:
"7 open issues remain. Priority: #2 (tests) or #6 (examples)"
This provided immediate context without needing to re-investigate.
mcp__github__list_issues(owner="rhea-impact", repo="taskr", state="open")
# Returns: 6 open issues (#1, #2, #4, #5, #6, #8)
Note: Down from 8 issues in Session 1. Issue #7 was closed previously.
Reviewed recent activity:
Issue #1 (README Overhaul):
mcp__github__add_issue_comment(
owner="rhea-impact", repo="taskr", issue_number=1,
body="""Completed! The README now includes:
- Logo and badges
- "Why Taskr?" value proposition
- Screenshots showing Taskr building Taskr
- "Taskr Learns Over Time" section with devlog explanation
- Deep Sleep preview (taskr-worker)
- Complete tool reference..."""
)
mcp__github__issue_write(
method="update", owner="rhea-impact", repo="taskr",
issue_number=1, state="closed", state_reason="completed"
)
Issue #2 (Test Coverage):
mcp__github__add_issue_comment(
owner="rhea-impact", repo="taskr", issue_number=2,
body="""Test infrastructure complete with 65+ tests:
- tests/core/test_task_service.py (17 tests)
- tests/core/test_devlog_service.py (16 tests)
- tests/core/test_session_service.py (18 tests)
- tests/mcp/test_github_tools.py (15 mocked tests)..."""
)
mcp__github__issue_write(
method="update", owner="rhea-impact", repo="taskr",
issue_number=2, state="closed", state_reason="completed"
)
devlog_add(
category="feature",
title="Session 2 - README polish and test coverage complete",
content="Continued work on rhea-impact/taskr...",
service_name="taskr",
tags=["rhea-impact", "session-2", "cleanup"]
)
taskr_session_end(
session_id="...",
summary="Closed #1 (README) and #2 (tests). 4 issues remain.",
handoff_notes="Remaining: #4 (PyPI), #5 (session tools), #6 (examples), #8 (hybrid search). Priority: #6 examples for user adoption."
)
| Metric | Session 1 | Session 2 |
|---|---|---|
| Time to complete | 1.5 min | 1.27 min |
| Issues closed | 1 | 2 |
| Issues updated | 2 | 0 |
| Devlogs created | 1 | 1 |
| Open issues after | 7 | 4 |
taskr_triage transformed a vague “clean up this project” request into a concrete 8-phase workflow that completed in 1.5 minutes. The key value is eliminating decision overhead - the agent doesn’t need to figure out what to do, it just executes the workflow.
Session 1 Session 2 Session N
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Work │──handoff──▶ │ Work │──handoff──▶ │ Work │
│ 8→7 open │ notes │ 6→4 open │ notes │ ... │
└─────────────┘ └─────────────┘ └─────────────┘
Each session:
This creates persistent memory across context windows.
For projects with many issues, the triage skillflow (triage-project-cleanup) automates the reconciliation between devlogs and GitHub issues, finding:
This case study demonstrates that structured workflows (via triage) enable rapid, consistent project management that would otherwise require significant cognitive overhead. The session continuity pattern ensures no work is lost between conversations.