understand
Skill32 starsChanged 32 days agoApache-2.0View on GitHub
Deep understanding mode (nemawashi) - exhaustive context-gathering before action
18 other projects use a version of this.
Adopted by
Most recently taken up by
- sogud/skillstheir own version, first seen Nov 8, 2026
- thoughtbot/rails-consultanttheir own version, first seen Nov 8, 2026
- taljeon/plzdotheir own version, first seen Nov 1, 2026
- stevepolitodesign/skillstheir own version, first seen Oct 14, 2026
- jayden-dang/skillstheir own version, first seen Oct 13, 2026
- fcescob/understandtheir own version, first seen Oct 13, 2026
Used with
Projects with it also use understand-chat, understand-dashboard and 5 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.
karanmrnSkillunderstand-chat
Use when you need to ask questions about a codebase or understand code using a knowledge graph
Also in 3 projects that use this
karanmrnSkillunderstand-dashboard
Launch the interactive web dashboard to visualize a codebase's knowledge graph
Also in 3 projects that use this
atopileSkillgraph
How the Zig-backed instance graph works (GraphView/NodeReference/EdgeReference), the real Python API surface, and the invariants around allocation, attributes, and cleanup. Use when working with low-level graph APIs, memory management, or building systems that traverse the instance graph.
Also in 3 projects that use this
AWSSkillship
Finalize dev work on an issue branch — update docs, push, and open a PR.
Also in 3 projects that use this
Google CloudSkilltriage
Gather context on a change or bug and plan the implementation.
Also in 3 projects that use this
- +2 more from karanmrn
Other versions18 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 18
- smallnest/goal-workflow★ 283same name
- thoughtbot/rails-consultant★ 29same name
- agoodway/.claude★ 11same name
- stevepolitodesign/skills★ 10same name
- taljeon/plzdo★ 9same name
- fcescob/understand★ 4same name
- digitaldreams/tuhin★ 3same name
- jkjackson2000/understand★ 2same name
- jayden-dang/skills★ 1same name
- manastalukdar/ai-devstudio★ 1same name
8 more not listed
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 repository19 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- 6hatsSkill
- ab-equivalenceSkill
- assess-findingsSkill
- assess-prSkill
- assessSkill
- deslopSkill
- fix-developSkill
- fix-prSkill
- ghreportSkill
- ghsyncSkill
- huddleSkill
- issuesSkill
- marathonSkill
- pr-review-mergeSkill
- semantic-compressSkill
- skill-forgeSkill
- tm-marathon-config-exampleSkill
- tmSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 16 edited versions we read keep these.
1
Distinctive
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 16
Consider what is unnecessary or removable - elimination and simplification are valid.
“Common” is measured: kept by at least 6 in 10 of the 16 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
Deep Understanding Mode
Lay groundwork before any solution. Create space for the true need to emerge; understand it fully, unpack complexity without rushing to solve. Reach an intuitive grasp of the core issue.
Disciplines:
- Strict focus on problem definition - no solution exploration. Reject solution discussions; request reframing when solutions appear in the problem statement.
- Question assumptions and vague terms with determination; challenge the framing, the scope, and whether the problem needs solving at all.
- Hold space for ambiguity until clarity emerges; attend to context.
- Consider what is unnecessary or removable - elimination and simplification are valid.
- Separate people from problems; look past stated positions to underlying interests; distinguish what people want from why. Reframe positions as shared interests; challenge either/or thinking; suggest objective criteria.
Core questions:
- What do we mean by [key terms]?
- What explicit and implicit needs exist?
- Who are the stakeholders, and what interests sit behind their positions?
- What defines success? What objective criteria would all stakeholders accept?
- What constraints and cultural/contextual factors matter?
- What is the gap between current and ideal state?
- What knowledge gaps need investigation?
- Could elimination serve better than a solution? What happens if we do nothing? What could be removed entirely?
Understanding is complete when: core terms are defined; explicit and implicit needs surfaced; scope bounded; success criteria and objective evaluation criteria agreed; stakeholders identified and aligned; assumptions documented and validated; current vs ideal state articulated; underlying interests surfaced and common ground established; and the problem statement is specific, measurable, and solution-independent, with no embedded solution.
Produce a provisional, solution-independent restatement of the problem - explicitly marked to-be-validated, not yet agreed.
Return to understanding when new assumptions or implicit needs surface, context shifts, understanding feels incomplete, solutions are proposed prematurely, the problem statement embeds a solution, or stakeholders are misaligned.
Apply to following statement:
Does it work?
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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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.

