From understood
Reword text into blunt, clipped, low-cognitive-load phrasing (drop articles, pronouns, helper verbs, use bare verbs, short plain words). Preserves the source's structure and ideas, only the wording changes. Use when the user invokes /caveman-english, asks to "caveman this", "make this blunt", "make this clipped", or wants a lower cognitive-load version of existing text. Operates on text the user pastes or references, never triggers proactively on Claude's own answers. Shared voice used by other "understood" patterns like forward-arrow.
How this skill is triggered — by the user, by Claude, or both
Slash command
/understood:caveman-englishThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Rewords text into blunt, clipped phrasing to cut reading and cognitive load, without changing what it says or how it's organized. Structure stays: same paragraphs, same bullets, same set of ideas. Only the wording changes.
Rewords text into blunt, clipped phrasing to cut reading and cognitive load, without changing what it says or how it's organized. Structure stays: same paragraphs, same bullets, same set of ideas. Only the wording changes.
This is a voice, not a compressor. If the goal is trimming the content itself down to a gist, that's a different job (see forward-arrow, which uses this voice for its chain steps but also decides what to cut).
= is fine for "means/becomes" ("fail = 400"). Avoid + for joining more than two things, and avoid stacking more than one symbol in a single clause. Once a sentence needs more than one symbol to parse, it reads as an equation, not caveman speech. When in doubt, use a plain short word ("with", "and") instead of a symbol.Input:
Before, we tried giving the search endpoint a new job: it would open the file itself, split it into chunks, run a prompt per chunk, and hand back all chunk answers in one call. The lead said no. The search endpoint's job is one query in, one result out. It must not touch files and must not know about documents, so we closed both changes and undid this from search. After, the search endpoint stays unchanged from before this whole effort. It still just has two jobs: lookup (query in, result out) and rank (results in, ordered list out). No new file-opening code lives on search at all. The chunking work moves to the ingest endpoint instead. Ingest is already file-aware by design, so the new chunking logic sits there now, not on search.
Output:
before: we try give search new job. give it open file itself, split into chunks, run prompt per chunk, hand back all chunk answers in one call.
lead say no. search job = one query in, one result out. search must not touch files, must not know about documents. so we close both change, undo this from search.
after: search endpoint unchanged from before this whole effort. still just two jobs, lookup (query in, result out) and rank (results in, ordered list out). no new file-opening code lives on search at all.
chunking work move to ingest endpoint instead. ingest already file-aware by design, so new chunking logic sit there now, not on search.
npx claudepluginhub bishwas-py/understood --plugin understoodGuides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.
Synthesizes the current conversation into a structured spec (PRD) and publishes it to the project issue tracker with a ready-for-agent label, without interviewing the user.