Beads Viewer

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Open

In Progress

Blocked

Actionable

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Dependency Graph

Visualize connections & find optimal paths

Quick Wins

High impact

All caught up!

No quick wins at the moment

Blockers to Clear

Blocking the most issues

No blocking issues

Your project flow is clear

By Type

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By Priority

No data

Top Picks

No issues to display

Start by creating some beads

Progress Over Time

Priority Distribution

Issues by Type

Label Dependency Heatmap

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Recent Activity

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Showing of issues

Page of

No matching issues

No results for "" No issues match the selected filters There are no issues to display

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Active Nodes

Graph Engine

Cycles

Actionable

Blocked

AI Priority Picks

Greedy optimization: maximize unblocks

potential unblocks

Cascade Impact Analysis

What-if: closing these unlocks the most downstream work

📈

Project Velocity

Work completion rate

Last 7 days
Last 30 days
Avg days

No weekly data available

🔬

Graph Health

Dependency structure

Nodes
Edges
Density
Cycles
Analysis

Circular Dependencies Detected

cycle(s) found in dependency graph

/

Current Cycle Path

Click "Highlight Cycles" to visualize dependency loops in the graph view.

Suggested Fixes

Remove these edges to break dependency cycles

8

Graph Analysis

Deep structural insights powered by graph algorithms

🚧

Bottlenecks

Betweenness Centrality

🚧
Bottlenecks
Betweenness Centrality
What It Measures

How often a bead lies on shortest paths between other beads in the dependency graph.

Why It Matters

High-scoring beads are critical junctions. Delays here ripple across the entire project.

Take Action

Prioritize these to unblock parallel workstreams. Consider breaking them into smaller pieces.

How It's Calculated
BW(v) = Σ (paths through v) / (total paths)
for all pairs of nodes s,t where s≠v≠t

📐 What: Measures how often a bead lies on shortest paths between other beads.

💡 Why: High-scoring beads are critical junctions. Delays here ripple across the entire project.

🎯 Action: Prioritize these to unblock parallel workstreams. Consider breaking them into smaller pieces.

No betweenness data available

🏛️

Keystones

Impact Depth

🏛️
Keystones
Impact Depth
What It Measures

How deep in the dependency chain a bead sits (downstream chain length).

Why It Matters

Keystones are foundational. Everything above them depends on their completion.

Take Action

Complete these first. Blocking a keystone blocks the entire chain above it.

How It's Calculated
Impact(v) = 1 + max(Impact(u))
for all u depending on v

📐 What: Measures how deep in the dependency chain a bead sits.

💡 Why: Keystones are foundational. Everything above them depends on their completion.

🎯 Action: Complete these first. Blocking a keystone blocks the entire chain above it.

No critical path data available

🌐

Influencers

PageRank / Eigenvector

🌐
Influencers
Eigenvector Centrality
What It Measures

Scores beads by their connections to other well-connected beads.

Why It Matters

Influencers are connected to important beads. Changes here have wide-reaching effects.

Take Action

Review carefully before changes. They're central to project structure.

How It's Calculated
EV(v) = (1/λ) × Σ A[v,u] × EV(u)
λ = largest eigenvalue, A = adjacency

📐 What: Scores beads by connections to other well-connected beads (eigenvector centrality).

💡 Why: Influencers are connected to important beads. Changes have wide-reaching effects.

🎯 Action: Review carefully before changes. They're central to project structure.

No PageRank data available

🚫

Most Blocking

Direct Blocker Count

🚫
Most Blocking
Direct Blocker Count
What It Measures

Issues that are directly blocking the most other issues from being worked on.

Why It Matters

Clearing these blockers enables parallel work on multiple dependent tasks.

Take Action

High-priority targets for immediate resolution to maximize team velocity.

How It's Calculated
Blocks(v) = count of issues where v is a blocker

📐 What: Issues directly blocking the most other issues from being worked on.

💡 Why: Clearing these enables parallel work on multiple dependent tasks.

🎯 Action: High-priority targets for immediate resolution to maximize velocity.

No blocking data available

🛰️

HITS Hubs

Aggregator Score

🛰️
HITS Hubs
Hub Score
What It Measures

Beads that depend on many important authorities (aggregators).

Why It Matters

Hubs collect dependencies. They often represent high-level features or epics.

Take Action

Track for milestones. Their completion signals major project progress.

How It's Calculated
Hub(v) = Σ Authority(u)
for all u where v→u

📐 What: Beads that depend on many important authorities (aggregators).

💡 Why: Hubs are coordination points. They represent high-level features or epics.

🎯 Action: Track for milestones. Their completion signals major project progress.

No HITS hub data available

📚

HITS Authorities

Provider Score

📚
HITS Authorities
Authority Score
What It Measures

Beads that are depended upon by many important hubs (providers).

Why It Matters

Authorities are foundational services/components that many features need.

Take Action

Stabilize early. Breaking an authority breaks many dependent hubs.

How It's Calculated
Auth(v) = Σ Hub(u)
for all u where u→v

📐 What: Beads depended upon by many important hubs (providers).

💡 Why: Authorities are foundational services that many features need.

🎯 Action: Stabilize early. Breaking an authority breaks many dependent hubs.

No HITS authority data available

🧠

K-Core Cohesion

Dense Clusters

🧠
K-Core Cohesion
k-core Number
What It Measures

Nodes with highest k-core numbers (embedded in dense subgraphs).

Why It Matters

High-core nodes sit in tightly knit clusters—changes can ripple locally.

Take Action

Use for resilience checks; prioritize when breaking apart tightly coupled areas.

How It's Calculated
k = max core that node remains in
after iterative degree peeling

📐 What: Nodes with highest k-core numbers (embedded in dense subgraphs).

💡 Why: High-core items are in tightly coupled clusters—changes ripple through the group.

🎯 Action: Handle together as a batch. They often form natural work packages.

No k-core data available

🪢

Cut Points

Articulation Vertices

🪢
Cut Points
Articulation Vertices
What It Measures

Nodes whose removal disconnects the undirected graph.

Why It Matters

Single points of failure. Instability here can isolate workstreams.

Take Action

Harden or split these nodes; avoid piling more dependencies onto them.

How It's Calculated
Tarjan's articulation algorithm
on undirected graph view

📐 What: Nodes whose removal disconnects parts of the dependency graph.

💡 Why: Single points of failure. Instability here can isolate workstreams.

🎯 Action: Consider adding parallel paths to reduce dependency on these critical bridges.

No cut points found (graph is well-connected)

Quick Wins

Low effort, high impact

No quick wins identified

🎯

Blockers to Clear

Unblock downstream work

No blockers identified

Triage Score Rankings

AI-computed priority scores combining multiple signals

Top Priority Issues

Score Distribution

High Priority (>0.7)
Medium (0.3-0.7)
Low Priority (<0.3)

Score Component Weights

🎯 PageRank
22%
🔀 Between.
20%
🚧 Blockers
13%
⭐ Priority
10%
⚡ Time
10%
🔥 Urgency
10%
⚠️ Risk
10%
⏰ Staleness
5%

AI Recommendations

Detailed analysis from robot-triage

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Fetching issues and dependencies PageRank, betweenness, clustering Setting up force-directed graph complete

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Tip: Use h and l to traverse the dependency chain. Navigate "left" to blockers and "right" to dependents.