Skill

Extract learnings from AI agent sessions into reusable fixes

Reconstructs the workflow behind a past coding-agent artifact by mining the local ax graph of commits, sessions, and skills.

Works with githubclaudecodexduckdb

91
Spark score
out of 100
Updated last month
Source checked Oct 4, 2026
Version 18.13.0

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Why it matters

Turn every AI coding agent session into institutional memory by watching what worked, what failed, and what got repeated-then converting that friction into reviewed, repo-specific improvements that make the next run smarter.

Outcomes

What it gets done

01

Ingest agent transcripts, git history, and tool calls into a local knowledge graph

02

Identify repeated mistakes and friction patterns across sessions

03

Generate structured retrospectives and improvement proposals for review

04

Track experiment verdicts and surface which skills actually earned their keep

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-ax-extract-workflow | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

Reports

Agent outcome reports

No reports yet

Overview

Reconstructs the workflow behind a shipped feature, PR, demo, or refactor by mining the local ax graph of commits, sessions, skills, and tool traces into a short evidence-grounded narrative with an ordered workflow, key decisions, and verification. Use it when someone asks how a past artifact was built and can name an anchor - a commit, date, feature, or repo - not for a generic activity summary.

What it does

This skill reconstructs the workflow behind a past coding-agent artifact - a shipped feature, PR, demo, refactor, or report - by using the local ax graph to connect commits, sessions, turns, skills, and tool traces into a short "how this got made" narrative. It works in four steps: resolve an anchor (commit SHA, date, feature name, or "this repo recently"), pick the few relevant sessions, inspect the session trail for skills used, steering points, files/tests/commands that changed direction, and verification steps, then write a short evidence-grounded reconstruction with an anchor, a 4-8 step ordered workflow, key decisions, verification, and a compact reproducer brief, citing session IDs, commit SHAs, and file paths where available.

When to use - and when NOT to

Use it when the user asks "how did we build X?", "what made X work?", or "extract the workflow behind this artifact", when the anchor is a commit SHA, date, feature name, PR, session, or repo-local artifact, or when the user wants the sequence of agent skills, prompts, commands, decisions, and checks that led to a result. Do not use it for a generic activity summary - use normal session listing instead. It reconstructs workflow, not correctness, so the code and project checks still need inspecting separately before making engineering decisions.

Inputs and outputs

Input is an anchor - a commit SHA, date or date range, topic/feature/artifact name, or "this repo recently" - resolved via read-only ax commands, for example:

ax recall "live ingest dashboard" --sources=turn,commit,skill --scope=here

Output is an inline (or, on request, file) reconstruction: the resolved anchor, an ordered 4-8 step workflow, key decisions, verification evidence, and a reproducer brief, citing session IDs, commit SHAs, and file paths.

Integrations

It requires a working local ax installation on PATH with a reachable local ax database; if ax cannot connect, the skill reports the connection failure and stops rather than guessing from memory. It only sees sessions, commits, skills, and tool traces that ax has already ingested, and session data can be incomplete when an agent provider omits tool output, cost, or reasoning data. Related skills: agenttrace-session-audit for session health/cost/latency/tool-failure audits, domain-modeling when the reconstruction reveals terminology or architecture worth capturing, and planning-with-files for turning the reconstructed recipe into a tracked plan.

Who it's for

Engineers and agents who need to explain or reproduce how a past artifact was actually built, working strictly from ax's own read-only inspection commands - never inventing missing skills, costs, commands, or decisions, and never uploading private transcripts, session logs, prompts, tool outputs, or local database exports. Secrets, tokens, customer data, and private conversation text are redacted from any summary, and the skill never mutates .ax/, regenerates indexes, publishes reports, or alters repositories as part of reconstruction.

FAQ

Common questions

Discussion

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