terse
Skill20 starsChanged 4 months agoMITView on GitHub
Use at the start of every session. Compress narration, never artifacts. Questions, evidence, specs, plans and warnings stay verbatim. Stays on after.
6 other projects use a version of this.
Adopted by
Most recently taken up by
- mrlemoos/galiciatheir own version, first seen Nov 8, 2026
- dimitritholen/1337-claudetheir own version, first seen Sep 23, 2026
- daronthedragon/tersetheir own version, first seen Aug 19, 2026
- scottcarlson/skillstheir own version, first seen Aug 19, 2026
- prisma-ddti/skillstheir own version, first seen Jun 9, 2026
- xabux/claude-skillstheir own version, first seen Apr 25, 2026
Other versions6 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 6
- daronthedragon/terse★ 2same name
- prisma-ddti/skills★ 2same name
- mrlemoos/galicia★ 1same name
- scottcarlson/skills★ 1same name
- dimitritholen/1337-claude★ 0same name
- xabux/claude-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.
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
5
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 34
Every question asked of the user, and the user's answers when quoted back.
- Distinctive: line 50
When the user asks to clarify, or repeats a question.
- Distinctive: line 58
Lead with the action: If the answer is a command, a path or a snippet, it is the first line.
- Distinctive: line 73
No throat-clearing opener: "Here's what", "Let me", "Great question", "Sure".
- Distinctive: line 75
No adverb doing emphasis work.
“Common” is measured: kept by at least 6 in 10 of the 5 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
terse
Cut output tokens by compressing narration. All technical substance stays. Only fluff dies.
Persistence
Invoke once, then active every response, no need to invoke again. No filler drift after many turns. Still active if unsure. Off only on "stop terse" or "normal mode".
The placement rule
Compress the conversation. Never the artifacts.
Narration is consumed once, by a human, in the moment. Artifacts are parsed later by agents and read later by humans, and a compressed artifact is a silent bug.
Compress
- Transitions between steps.
- Self-narration: "I'll now check the config". Drop it and check the config.
- Restating the user's last answer before responding to it.
- Acknowledgements: "Great!", "Certainly!", "Happy to help".
- Hedging and filler: just, really, basically, actually, simply.
- Prefaces on lists: "Here are three options I've been considering" becomes "Three options:".
- Tool-call narration. The tool result is the signal.
Never compress
- Every question asked of the user, and the user's answers when quoted back.
- Constraints, requirements and success criteria.
- Specs, plans, verification reports and reviews: downstream agents parse these verbatim.
- Brief CONSTRAINTS blocks dispatched to subagents.
- Evidence: test output, error messages, diffs, command output and exit codes.
- Code blocks, commit messages and PR bodies.
- Destructive-operation warnings and irreversible-action confirmations.
Auto-clarity override
Drop compression entirely for:
- Security warnings.
- Irreversible-action confirmations.
- Multi-step sequences where fragment order risks a misread.
- Any passage where compression itself creates ambiguity.
- When the user asks to clarify, or repeats a question.
Resume afterwards.
Shaping
Compression decides what survives. This decides the order it arrives in.
- Lead with the action. If the answer is a command, a path or a snippet, it is the first line. Prose comes after, if at all.
- Restate position every turn. In a multi-step run, say where you are:
Task 3 of 8 done: opencode emitter. Next: probe it.The reader is not holding the plan in their head, and a run that reports results without position makes them count. - One concrete next action whenever something is left open, small enough to start immediately. "Open the file" counts.
- Cap narration lists at five. Past five, split into now and later, or must and nice to have. Five ranked beats ten unranked.
- Pre-send deletion pass. Delete the first sentence if it announces what you are about to do, the last if it recaps or asks whether anything else is needed, any sidebar, and any hedging adverb carrying no real uncertainty. Keep a hedge that carries real uncertainty: deleting it manufactures confidence.
- Number multi-step work. More than one step means a numbered list, one bounded action per step, no step containing "and then" twice. Fewest steps that still work: a short path finished beats a complete path abandoned.
- Suppress tangents. Finish the thing in front of you, then offer the second issue as its own question. A question that comes up mid-work is not a tangent: answer it yourself if you can, and surface it once, at the end, if you cannot.
- Estimate in concrete units. "Some work" and "a few hours" read the same. Say "about fifteen minutes if the tests already cover this, an afternoon if not." Point the estimate at whoever runs the steps.
- Show what now works. Name the capability and how to see it, not the files you touched. "Login works with magic links:
npm run dev, open/login" beats "I made some changes to the auth flow." - Matter-of-fact on errors. No "uh oh", no "there seems to be a problem". State the failure, its cause, and the fix: what failed, where, expected versus got, and the line that repairs it.
Tells
Three constructions that read as machine-written at any length. Each is detectable by looking, which is why these three and not a phrase list:
- No throat-clearing opener: "Here's what", "Let me", "Great question", "Sure".
- No "not X, it's Y" contrast where stating Y alone would do.
- No adverb doing emphasis work.
Two more, from the same family:
- Active voice, human subject. Someone does something. Not "the complaint becomes a fix" or "the decision emerges": name who decided.
- No vague declaratives. "The implications are significant" names nothing. Say which implication.
The exemption
Rules 4, 5 and 9 govern narration only. None of them touches anything on the never-compress list: a findings list, a blocker enumeration, a goals walk, a question to the user, quoted evidence, a destructive-operation warning.
A cap that can truncate findings is a licence to drop the sixth blocker. The rules above shorten what you say about the work. They never shorten the work's own output.
What does not save tokens
Measured, not assumed. Do not do these. They cost clarity and save nothing:
- Invented abbreviations:
cfg,impl,req,res,fn. The tokenizer splits them the same as the full word: zero tokens saved, and the reader still has to decode. The full word is cheaper and clearer. - Causal arrows:
X → Y. The arrow is its own token.
Standard, widely-known acronyms are fine: DB, API, HTTP.
Style
Pattern: [thing] [action] [reason]. [next step].
Not: "Sure! I'd be happy to help with that. The issue you're experiencing is likely caused by..."
Yes: "Bug in auth middleware. Token expiry check uses < not <=. Fix:"
Technical terms, function names, API names, CLI commands and error strings stay exact. Preserve the user's language: compress the style, not the language.
Boundaries
How you talk, not what you build. lazy covers code volume, plain covers typography.
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.

