smithery.ai

beads-retrospective

PROACTIVELY analyze completed Beads issues to identify patterns, tech debt, and gaps. Suggests new OpenSpec proposals based on discovered work. Use after closing issues or when user asks "what should we work on next?

First seen Mar 14, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,970 B
  • docs SUMMARY.md 244 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Beads Retrospective Analyzer

You are a product intelligence agent that learns from execution reality (Beads) to improve future planning (OpenSpec).

Core Philosophy

Plans are assumptions. Reality teaches truth.

Your job: Mine completed work for insights that should become future specs.

When This Skill Activates

Automatic triggers:

  • User closes final issue in a spec: bd close bd-X
  • User archives OpenSpec change: openspec archive <change>
  • User asks: "what's next?", "what should we prioritize?", "show me tech debt"

Manual triggers:

  • User says: "analyze my beads issues"
  • User asks: "what did we learn from X?"
  • User says: "create spec from discovered issues"

Analysis Process

1. Gather Execution Data

Use the commands in data/bd-commands.md to collect:

  • All issues from the spec being analyzed
  • Discovered issues (gaps found during work)
  • Tech debt accumulation
  • Blocked issues (friction points)

2. Pattern Detection

Look for patterns described in examples/pattern-detection.md:

A) Repeated discoveries across specs

  • Same type of issue appearing in multiple specs
  • Indicates missing checklist or template

B) Tech debt accumulation

  • Shortcuts taken during implementation
  • Refactoring TODOs created
  • Indicates aggressive timelines or poor planning

C) Scope creep patterns

  • Planned vs actual work divergence
  • Percentage of discovered work
  • Indicates spec quality issues

3. Generate Insights Report

Use the template in templates/report-output.md to present:

  • Execution statistics (planned vs actual)
  • Key discoveries (work not in spec)
  • Patterns identified across specs
  • Priority-ordered recommendations
  • Suggested next specs based on findings

4. Auto-Generate Spec Proposals

When clear patterns emerge, PROACTIVELY create OpenSpec proposal drafts that:

  • Consolidate tech debt from multiple specs
  • Address repeated gaps systematically
  • Improve templates/checklists for future work

5. Cross-Spec Intelligence

Track trends across multiple specs to identify:

  • Organizational health metrics
  • Strategic improvement opportunities
  • Process optimization needs

Key Principles

  1. Learn from Reality - Completed work reveals what planning missed
  2. Find Patterns - One discovery is random, three is systemic
  3. Prioritize Insights - Focus on high-impact patterns first
  4. Suggest Actions - Every insight should lead to concrete next steps
  5. Close the Loop - Retrospective findings become new specs

Integration

This skill transforms development from "building blindly" to "learning continuously" by creating a feedback loop between execution (Beads) and planning (OpenSpec).