regression-bisect
Skill1 starsChanged 8 months agoMITView on GitHub
Team E diagnostic — regression hunting for features that stopped working. Git bisect, side effect analysis, rollback verification.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- matthewcsimpson/agentic-playbookstheir own version, first seen Jun 24, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- matthewcsimpson/agentic-playbooks★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 92
If no breaking commit found in recent history: escalate to Team B (might be infrastructure, not code).
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Regression Bisect (Team E)
For when something used to work and now doesn't. Finds the breaking change and its unintended side effects.
When to Use
- Directly: when user says "this used to work" or "it broke after [change]"
- Via router:
/persistent-issueclassifies as Category E
Input
- Evidence Document from
/persistent-issue - Approximate timeframe when it last worked (if known)
Agent Team (Sequential Pipeline, all model: "opus")
Agent 1: Git Bisector
Find the commit range where the issue was introduced.
Evidence: [paste Evidence Document]
Steps:
1. Identify the affected feature/component/endpoint
2. Run `git log --oneline --since="2 weeks ago" -- [affected files]` to see recent changes
3. If user provided a timeframe: `git log --oneline --after="[date]" -- [affected files]`
4. For each commit in the range:
- Read the diff: `git show [hash] --stat` then `git show [hash] -- [specific file]`
- Could this change have affected the broken feature?
5. Narrow to the most likely 1-3 commits
Do NOT use `git bisect` (requires interactive mode). Use manual diff analysis.
Output: Most likely breaking commit(s) with hash + summary of what changedAgent 2: Side Effect Analyzer
Analyze the suspected breaking commit for unintended side effects.
Evidence: [paste Evidence Document + Agent 1 findings]
Breaking commit: [hash from Agent 1]
Steps:
1. Read the FULL diff of the breaking commit: `git show [hash]`
2. For each changed file:
- Was the change intentional for the commit's stated purpose?
- Does the change affect any OTHER feature besides what the commit intended?
3. Check for these common side effect patterns:
- Shared utility change that affects multiple consumers
- CSS change with broader selector than intended
- Props change that breaks a different component
- Import change that shifts module initialization order
- Removed or renamed export that another file depends on
- Cache key pattern change that breaks cache reads
- API response shape change that breaks frontend parsing
4. Check if the commit modified shared files that affect multiple projects
Output: The specific side effect + which code path it breaksAgent 3: Rollback Verifier
Verify that reverting the suspected change would fix the issue WITHOUT actually reverting.
Evidence: [paste Evidence Document + Agent 1-2 findings]
Breaking commit: [hash]
Side effect: [from Agent 2]
Steps:
1. Read the current state of the affected code
2. Read the state BEFORE the breaking commit: `git show [hash~1]:[file]`
3. Identify the minimal change needed to fix the side effect WITHOUT reverting the whole commit
4. Verify the fix wouldn't break the commit's original purpose
The goal is a TARGETED fix, not a full revert:
- If a shared util was changed: can we fix the specific consumer that broke?
- If a CSS selector was broadened: can we narrow it without losing the intended styling?
- If a prop was removed: can we add it back where needed?
Output: Minimal targeted fix with exact code change at [file:line]Synthesis
Main agent presents: "The regression was introduced in commit [hash] ([message]). The commit intended to [purpose], but as a side effect it [broke X]. The fix is [targeted change] at [file:line] — this preserves the original commit's purpose while fixing the regression."
If no breaking commit found in recent history: escalate to Team B (might be infrastructure, not code).
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

