deepen
Skill23 starsChanged 2 months agoMITView on GitHub
Use when the user wants to know where the design is hurting, before choosing what to fix: \"this is getting messy\", \"where should we clean up?\", \"what is the worst part of this codebase?\", \"why is this so hard to change?\", \"it takes five files to add one field\". Surveys an area, ranks the candidates, and the user picks one. Not for a diff you just wrote: that is code-reviewer. Not for executing a chosen restructure: that is the refactorer agent.
10 other projects use a version of this.
Adopted by
Most recently taken up by
- hideki5123/agent-skill-settheir own version, first seen Nov 1, 2026
- nino-chavez/agentic-ways-of-workingtheir own version, first seen Oct 13, 2026
- krixon/skillstheir own version, first seen Oct 11, 2026
- mattbutlerengineering/skillstheir own version, first seen Oct 11, 2026
- Seanathon/vault-startertheir own version, first seen Sep 28, 2026
- SubliminalCoding/bilbroswagginz-skillstheir own version, first seen Sep 27, 2026
Used with
Projects with it also use zoom-out, diagnose and 1 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
victorgarciaesgiSkillzoom-out
Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.
Also in 3 projects that use this
MicrosoftSkilldiagnose
Use to systematically diagnose why scenarios fail — identifies root causes by analyzing agent traces, codebase, and behavioral patterns
Also in 3 projects that use this
GoogleSkilltdd
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
Also in 3 projects that use this
Other versions10 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 10
- JuliusBrussee/cavekit★ 1.1ksame name
- Brianhkerr/deepen-skill★ 3same name
- hideki5123/agent-skill-set★ 2same name
- nino-chavez/agentic-ways-of-working★ 2same name
- bdunn313/repolab★ 1same name
- krixon/skills★ 1same name
- mattbutlerengineering/skills★ 1same name
- qmertesdorf/GameForge★ 0same name
- Seanathon/vault-starter★ 0same name
- SubliminalCoding/bilbroswagginz-skills★ 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.
In this repository34 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- analyzeSkill
- assessSkill
- blueprintSkill
- breakdownSkill
- buildSkill
- checklistSkill
- clarifySkill
- constitutionSkill
- convergeSkill
- debugSkill
- deprecateSkill
- double-checkSkill
- explainSkill
- handoffSkill
- helpSkill
- initSkill
- interviewSkill
- learnSkill
- levelupSkill
- lintSkill
- living-docsSkill
- performanceSkill
- personaSkill
- promptSkill
- prototypeSkill
- qaSkill
- quarantineSkill
- reportSkill
- roadmapSkill
- routeSkill
- signatureSkill
- specifySkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 7 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 28
Not ugliness. Cost. Each of these has a named future price:
- Very specific: line 64
If the reasoning would stop the same candidate being re-proposed later, add a line to .mastermind/brief.md.
- Distinctive: line 69
Taste is not a cost: If you cannot name the future event, the candidate is not a finding.
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
MasterMind: Deepen
Find where the design costs the most, present the candidates, let the user choose. You survey and
rank. You do not restructure: the chosen one goes to the refactorer agent, which is where the edits
happen and where behaviour is proven unchanged.
Load ~/.mastermind/engineering/core/principles.md and mindset.md for the vocabulary. Read the
field's audit-rules.md and .mastermind/brief.md if they exist: with no field pack you still
have the universal principles, and with no brief you use the codebase's own names.
Scope it before you read anything
A whole-repo survey produces a list nobody acts on. Narrow first:
- Take the area the user named. If they named none, use
git logto find what changed most in the last few months. Design debt hurts where the code moves. - Cap it. Six candidates maximum, and fewer is better.
- Send the reading to a subagent where you have one, so the survey does not eat this context. Where you do not, read in the same order and keep notes short: the cap is what protects the context.
What you are looking for
Not ugliness. Cost. Each of these has a named future price:
- A shallow module: the interface costs about as much to understand as the implementation it hides. It adds a name and buys nothing.
- A concept spread thin: understanding one idea means opening five files. The split was mechanical, not conceptual.
- A leaked boundary: callers know the shape of what is behind the seam, so the seam cannot move.
- A path that cannot be tested without standing up the world, because there is nowhere to substitute.
- An invariant enforced in several places, which will drift, because one day someone edits four of five.
Apply the deletion test to anything suspected shallow: if this module disappeared and its callers did the work inline, would the code get worse? If the honest answer is no, that is the finding.
Present them as a choice, not a report
One block per candidate, ranked, in plain text. Use the forms in
~/.mastermind/engineering/core/clarity.md: a tree, a call flow, a before and after. Plain text over a
rendered diagram, because it reads faster and works in every tool.
Each candidate carries five things and nothing else:
- Where: the files, with line numbers.
- The cost, as a future event: "adding a fourth provider means editing all five call sites." Never a feeling, never "this is ugly".
- The shape after, drawn.
- What it buys: fewer places to hold in your head, or a seam a test can enter.
- Confidence: strong, or worth-discussing. Say which, and say why for the weak ones.
Then one line naming your recommendation and the reason. Then stop, and let them pick.
After they pick
Hand it to the refactorer agent with the contract from core/agent-loop.md: the goal, the non-goals,
the stopping condition, and the evidence it must return. Behaviour is preserved and proven green, or the
change does not land.
If the reasoning would stop the same candidate being re-proposed later, add a line to
.mastermind/brief.md. Only then: a decision nobody would re-litigate is not worth the space.
Gotchas
- Taste is not a cost. If you cannot name the future event, the candidate is not a finding. Drop it.
- Do not survey a diff. A change you just made goes to
code-reviewer. This reads code that already shipped. - Do not propose a rewrite. A candidate a person can review is worth more than a correct plan they cannot.
- Shallow is not small. A three-line function with an obvious name is fine. The test is whether the interface is as complex as what it hides.
- Never edit here. Finding and fixing in one pass is how a survey turns into an unreviewable diff.
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.

