deliverable-language
Skill3 starsChanged 17 days agoMITView on GitHub
Write deliverables in the language the user is speaking, and pin one rendering per concept so terminology stays stable across runs. Covers picking the language without asking, recording term choices in the authoritative document, and keeping a translated vocabulary consistent. Use whenever a skill produces written artifacts for a user whose language may not be the skill body's language.
In this repository15 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- constraint-by-typesSkill
- decision-interviewSkill
- decision-recordSkill
- spec-before-codeSkill
- ui-contract-assetsSkill
- ui-contract-auditSkill
- ui-contract-baselineSkill
- ui-contract-designSkill
- ui-contract-enforceSkill
- ui-contract-glossarySkill
- ui-contract-layoutSkill
- ui-contract-setupSkill
- ui-contractSkill
- ui-contract-wireframeSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
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 12
Write the deliverables in the language the user is speaking.
- Distinctive: line 22
If the invoking skill ships a canonical term table for the user's language, use those exact terms.
- Distinctive: line 23
If it doesn't, pick one rendering per concept, write your choices into a glossary section of the authoritative document, and stay …
≈ “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
Deliverable language
Skill bodies are written in one language. Deliverables follow the user's. Those are different questions and they get different answers.
Pick it, don't ask
Write the deliverables in the language the user is speaking. Do not ask which language they want, and do not make it a configuration option — just follow them.
Asking implies it is negotiable and costs a turn on something you can already observe.
Pin one rendering per concept
The failure mode this exists to prevent is concrete: the same concept gets translated differently on every run, so two projects — or two agents on one project — end up unable to talk to each other. One writes it one way, the next writes it another, and neither is wrong in isolation.
So:
- If the invoking skill ships a canonical term table for the user's language, use those exact terms. Don't improve on them; consistency is worth more than a better word.
- If it doesn't, pick one rendering per concept, write your choices into a glossary section of the authoritative document, and stay consistent for the rest of the project.
That glossary section is not decoration. It is what lets the next run — or the next agent — reuse your vocabulary instead of inventing a parallel one.
What stays untranslated
Identifiers that the code or a machine consumes — type names, keys, attribute values, file names — stay in their original form regardless of the deliverable's language. Translating a name that something greps for breaks the thing the name existed for.
The human-readable label next to such an identifier does get translated. The identifier itself never does.
Mixed-language projects
If the project's existing documents are in one language and the user is speaking another, say what you found and let them choose; don't silently switch a project's language halfway through. Matching the existing documents is usually right, but that is their call, not yours.
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.

