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SKILL verified Apache-2.0 Self-run

Synthesis Project Management

skill-synthesisengineering-synthesis-skills-synthesis-project-management · by synthesisengineering

Lightweight project management system designed for human-agent collaboration, optimized for context preservation across sessions. Use when asked to: project management, project setup, project tracking, synthesis project, manage project, set up project, project structure, session protocol.

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Install

$ agentstack add skill-synthesisengineering-synthesis-skills-synthesis-project-management

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Synthesis Project Management System

A lightweight project management system designed for human-agent collaboration. Optimized for context preservation across conversation sessions and context compaction events.

Configuration

These values are user-specific. Update them for your environment.

| Setting | Value | Description | |---------|-------|-------------| | ai_knowledge_workspace | ai-knowledge-{workspace} | Root directory for your ai-knowledge repo (e.g., ai-knowledge-rajiv) | | projects_path | projects/ | Directory within the workspace for all project folders | | index_file | projects/index.yaml | Single index file for all projects | | lessons_path | lessons/ | Cross-project lessons and patterns directory |


Design Principles

  1. Discoverability over documentation — Agents can search/grep; humans need quick orientation. Prefer consistent naming conventions over maintained indexes.
  2. Convention over configuration — Consistent structure means less cognitive load. When everything follows the same pattern, both humans and agents know where to look.
  3. Single source of truth — No duplicate indexes to maintain. Files should be self-describing through front matter and naming conventions.
  4. Self-describing files — Date prefixes, status in index.yaml, front matter metadata. No separate documentation that can get stale.
  5. Agents do the work — Templates are obsolete. To create something new, examine an existing example and adapt it. Agents excel at this.

Problem This Solves

When working with AI assistants on multi-session projects:

  • Context compaction (conversation summarization) loses detailed progress
  • Session boundaries create information gaps
  • Tool switching between Claude Code, Codex, Cursor, and other agents can strand context in tool-specific transcripts
  • Multiple projects create confusion about current state
  • Lessons learned get lost instead of compounding

This system provides persistent state that survives context loss.

The project files are the durable memory layer. Treat chat history, model memory, and compaction summaries as helpful but insufficient. A user should be able to pause in one capable agent environment, open the same project in another, read the project context, and continue.


System Architecture

All project management lives in one location within your ai-knowledge workspace:

ai-knowledge-{workspace}/
└── projects/
    ├── index.yaml               # Single index for ALL projects (status field, not folders)
    │
    ├── {project-id}/            # Project folders (flat structure)
    │   ├── CONTEXT.md           # Working memory — active state (budget: ≤150 lines)
    │   ├── REFERENCE.md         # Semantic memory — stable facts (updated in place)
    │   ├── sessions/            # Episodic memory — archived session logs
    │   │   └── YYYY-MM.md       #   Monthly files
    │   ├── README.md            # Static documentation (optional)
    │   └── resources/           # Project data and artifacts (optional)
    │       ├── in/              # Inputs
    │       ├── artifacts/       # Working data
    │       ├── out/             # Outputs
    │       └── scripts/         # One-off scripts
    │
ai-knowledge-{workspace}/
└── lessons/                    # Cross-workspace lessons (top-level, no underscore, ADR-017)
    └── YYYY-MM-DD-*.md         # Date-prefixed for discoverability

Key Structural Decisions

| Decision | Rationale | |----------|-----------| | Flat project folders | Status is in index.yaml, not folder names. No moving folders when status changes. | | lessons/ at top level (no underscore) | Lessons are a peer content domain to projects, not a sub-component. Top-level layout matches semantic equality (ADR-017). | | Three-tier context | CONTEXT.md (working memory), REFERENCE.md (stable facts), sessions/ (history). See the synthesis-context-lifecycle skill. | | Date-prefixed lesson files | Enables time-based discovery. ls -t shows recent. No index needed. | | No templates folder | Agents examine existing examples and adapt. Templates are a pre-AI pattern. | | No patterns.md | Patterns are lessons with type: pattern in front matter. One folder to search. |


Components

1. Project Index (index.yaml)

Single source of truth for all projects. Status is a field, not a folder.

# Projects Index
# Last updated: YYYY-MM-DD

# Status values:
#   active    - Currently being worked on
#   paused    - Started but on hold
#   ongoing   - Continuous/maintenance work, no defined end state
#   completed - Has defined deliverables that are done
#   archived  - Old/obsolete, kept for reference only

projects:
  - id: my-project
    name: My Project Name
    status: active
    description: Brief description of what this project accomplishes
    tags:
      - tag1
      - tag2
    last_session: YYYY-MM-DD

  - id: finished-project
    name: Finished Project
    status: completed
    completed_date: YYYY-MM-DD
    description: What was accomplished
    tags:
      - tag1
    outcome: success
    key_result: Brief summary of what was delivered

Update when: Session end (update last_session), project status changes, new project added.

2. Tiered Context Architecture

Projects use a three-tier context system that separates information by lifecycle. This prevents unbounded growth of context files and keeps AI collaborators effective across long-running projects.

Detailed documentation: See the synthesis-context-lifecycle skill for templates, migration guides, decision trees, and quality metrics.

The three tiers:

| Tier | File | Purpose | Budget | Update pattern | |------|------|---------|--------|---------------| | Working memory | CONTEXT.md | Current state, active tasks, recent sessions | ≤150 lines (hard) | Every session | | Semantic memory | REFERENCE.md | Stable facts (team, URLs, architecture) | ≤300 lines (soft) | Updated in place when facts change | | Episodic memory | sessions/YYYY-MM.md | Archived session logs | No budget | Append-only, monthly files |

Archival protocol: At session start, if CONTEXT.md exceeds 120 lines: archive completed tasks and old session logs to sessions/, move stable facts to REFERENCE.md, verify content exists in destination, then remove from CONTEXT.md. Archive FIRST, delete second — two-phase commit.

3. Lessons (lessons/)

Cross-project mistakes, insights, and patterns. All in one folder with date prefixes.

File naming: YYYY-MM-DD-topic-slug.md

For incidents/mistakes:

---
type: incident
title: Brief Title
severity: minor | moderate | serious | critical
---

# {Topic}: {Brief Title}

## What Happened
## Root Cause
## Impact
## Lesson
## Prevention

For patterns (generalized insights):

---
type: pattern
title: Pattern Name
---

# {Pattern Name}

## Context
## Problem
## Solution
## Examples

Update when: Immediately when you learn something reusable.


The Protocol

During Work

Complete task → Update CONTEXT.md → Commit → Next task

NOT:

Complete task → Complete task → Complete task → (context compaction) → Lost details

Session Start

  1. Read CONTEXT.md — Understand current state before touching code
  2. Check line count — If CONTEXT.md >150 lines, archive before starting work
  3. Read REFERENCE.md — If it exists and the task needs reference details
  4. Search lessons/grep for relevant past experiences
  5. Check related projects — Look at related: tags in index.yaml

Session End

  1. Final CONTEXT.md update — Ensure all sections current (≤150 lines)
  2. Archive if needed — Move old sessions to sessions/, stable facts to REFERENCE.md
  3. Update index.yaml — Set last_session date
  4. Commit all changes — Do not leave uncommitted work

Cross-Agent Handoff

Before pausing work that may continue in another tool:

  1. Update CONTEXT.md with current state, decisions, and next actions
  2. Move stable facts into REFERENCE.md
  3. Append chronological detail to sessions/YYYY-MM.md
  4. Save substantial plans, audits, or checklists under resources/artifacts/
  5. Commit and push the project-management changes

When resuming work from another agent, trust the project files over tool-specific memory. The continuity source of truth is the synthesis project context, not the previous assistant's chat transcript.


File Requirements by Project Status

| Status | CONTEXT.md | REFERENCE.md | sessions/ | CONTEXT.md budget | |--------|------------|-------------|-----------|------------------| | active | Required | When needed | When needed | ≤150 lines | | paused | Required | When needed | When needed | ≤150 lines | | ongoing | Required | When needed | When needed | ≤150 lines | | completed | Required (summary) | Optional | Optional | ≤80 lines | | archived | Frozen | Frozen | Frozen | N/A |


Project Discovery

When a user mentions a project:

  1. Read projects/index.yaml
  2. Match user's phrase against project name, description, id, tags
  3. If match found, read the project's CONTEXT.md
  4. Summarize current state and next steps
  5. Begin work from where it left off

Common Mistakes

| Mistake | Consequence | Prevention | |---------|-------------|------------| | Not updating CONTEXT.md | Lost progress after compaction | Update after EVERY task | | Deferring updates to "session end" | Forget to update | Update immediately | | Putting management files in project repos | Exposes internal process | Keep in ai-knowledge-{workspace} | | Not checking lessons/ | Repeat mistakes | Grep at session start | | Creating separate patterns.md | Duplicate, gets stale | Use type: pattern in lessons/ | | Maintaining index files for lessons | Gets stale | Use date prefixes, ls -t |


Why This Works

  1. Filesystem is persistent — Survives context compaction
  2. Convention-based — Same structure everywhere, easy to navigate
  3. Tiered by lifecycle — Hot data in CONTEXT.md, warm in REFERENCE.md, cold in sessions/
  4. Budgeted — 150-line cap prevents degradation over time
  5. Self-maintaining — Archival protocol is garbage collection for context
  6. Searchable — Agents grep, humans ls -t
  7. Scales — Tested across 60+ projects over months of continuous use

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.